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<p><span style="font-weight: 400;">D-Plex DNBSEQ</span> <span style="font-weight: 400;">Barcodes - Set A <span>includes primers with </span><span>24</span><span><span> barcodes</span> to enable multiplexing</span><span> with</span> the </span><a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24">D-Plex Small RNA DNBSEQ<sup>TM</sup> Kit</a><span style="font-weight: 400;">. They were designed and validated to fit the D-Plex technology for MGI sequencers.</span></p>
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<p><span style="font-weight: 400;"><span>Read more about the </span><a href="https://www.diagenode.com/en/categories/Library-preparation-for-RNA-seq">D-Plex technology</a><b>.</b></span></p>',
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<p><span style="font-weight: 400;">D-Plex DNBSEQ</span><span><span> </span></span><span style="font-weight: 400;">Barcodes - Set B<span> </span><span>includes primers with </span><span>24</span><span><span> barcodes</span> to enable multiplexing</span><span> with</span> the<span> </span></span><a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24">D-Plex Small RNA DNBSEQ<sup>TM</sup><span> </span>Kit</a><span style="font-weight: 400;">. They were designed and validated to fit the D-Plex technology for MGI sequencers.</span></p>
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<p>Diagenode’s MicroChIP DiaPure columns have been optimized for the purification and elution of very low amounts of DNA. This rapid method has been validated for epigenetic applications like low input ChIP (e.g. using the True MicroChIP kit) and CUT&Tag (e.g. using Diagenode’s pA-Tn5), but is also compatible with many other applications. The DNA can be eluted at high concentrations in volumes down to 6 μl and it is suitable for any downstream application (e.g. NGS).</p>
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<p><img src="https://www.diagenode.com/img/product/kits/figure-igv-microchip.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1:</strong> Integrative genomics viewer (IGV) visualization of ChIP-seq experiments using 50,000 of K562 cells.</p>
<p></p>
<h2 style="text-align: center;"></h2>
<h2 style="text-align: center;">MicroChIP DiaPure columns after CUT&Tag</h2>
<p>Successful CUT&Tag results showing a low background with high region-specific enrichment has been generated using 50.000 of K562 cells, 1 µg of H3K27me3 antibody (Diagenode, Cat. No. C15410069) and proteinA-Tn5 (1:250) (Diagenode, Cat. No. C01070001). 1 µg of IgG (Diagenode, Cat. No. C15410206) was used as negative control. Samples were purified using the MicroChIP DiaPure columns or phenol-chloroform purification. The below figure presenst the comparison of two purification methods.</p>
<p><img src="https://www.diagenode.com/img/product/kits/figure-diapure-igv.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 2:</strong> Integrative genomics viewer (IGV) visualization of CUT&Tag experiments: MicroChIP DiaPure columns vs phenol-chloroform purification using the H3K27me3 antibody.</p>',
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<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integration into numerous transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
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<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes two innovative <strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong> - to produce sequencing libraries from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs. Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time. <span>The library preparation takes place in a </span><strong>single tube</strong><span>, increasing the efficiency tremendously. </span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span> - D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span> - D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex Unique Dual Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex Unique Dual Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended to mitigate errors introduced by read misassignment, including index hopping frequently observed with patterned flow cells such as Illumina’s NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
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<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
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<p></p>
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<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM ≥5, as shown above for different species.</p>
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</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
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<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
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<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
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<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R² > 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
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<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
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<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3’-end and primed with an oligo(dT) primer containing part of the ILMN 3’-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5’-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
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'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p> </p>
<p> </p>
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<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for <span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
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<p> </p>
<p> </p>',
'label3' => 'Data analysis - Counting using MGcount',
'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select “stranded mode” in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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<p>将 <input name="data[Cart][quantity]" placeholder="1" value="1" min="1" style="width:60px;display:inline" type="number" id="CartQuantity" required="required"/> <strong> D-Plex DNBSEQ Barcodes for MGI Sequencing - Set B</strong> 添加至我的购物车。</p>
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'description' => '<div class="small-12 medium-12 large-12 columns" style="border: 3px solid #B02736; padding: 10px; margin: 10px;">
<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integration into numerous transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
</ul>
</div>
<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes two innovative <strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong> - to produce sequencing libraries from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs. Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time. <span>The library preparation takes place in a </span><strong>single tube</strong><span>, increasing the efficiency tremendously. </span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span> - D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span> - D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex Unique Dual Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex Unique Dual Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended to mitigate errors introduced by read misassignment, including index hopping frequently observed with patterned flow cells such as Illumina’s NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
'label1' => 'Characteristics and library prep. workflow ',
'info1' => '<div class="row">
<div class="small-12 columns">
<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM ≥5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R² > 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3’-end and primed with an oligo(dT) primer containing part of the ILMN 3’-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5’-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
</div>
</div>
<p><br /><br /></p>
<p></p>
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'label2' => 'Data analysis',
'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p> </p>
<p> </p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for <span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p> </p>
<p> </p>',
'label3' => 'Data analysis - Counting using MGcount',
'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select “stranded mode” in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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include - APP/View/Products/view.ctp, line 755
View::_evaluate() - CORE/Cake/View/View.php, line 971
View::_render() - CORE/Cake/View/View.php, line 933
View::render() - CORE/Cake/View/View.php, line 473
Controller::render() - CORE/Cake/Controller/Controller.php, line 963
ProductsController::slug() - APP/Controller/ProductsController.php, line 1052
ReflectionMethod::invokeArgs() - [internal], line ??
Controller::invokeAction() - CORE/Cake/Controller/Controller.php, line 491
Dispatcher::_invoke() - CORE/Cake/Routing/Dispatcher.php, line 193
Dispatcher::dispatch() - CORE/Cake/Routing/Dispatcher.php, line 167
[main] - APP/webroot/index.php, line 118
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<p><img src="https://www.diagenode.com/img/product/kits/figure-igv-microchip.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1:</strong> Integrative genomics viewer (IGV) visualization of ChIP-seq experiments using 50,000 of K562 cells.</p>
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<h2 style="text-align: center;"></h2>
<h2 style="text-align: center;">MicroChIP DiaPure columns after CUT&Tag</h2>
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<p><img src="https://www.diagenode.com/img/product/kits/figure-diapure-igv.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 2:</strong> Integrative genomics viewer (IGV) visualization of CUT&Tag experiments: MicroChIP DiaPure columns vs phenol-chloroform purification using the H3K27me3 antibody.</p>',
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<h2>Product Features</h2>
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<li>Versatile integration into numerous transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
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<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes two innovative <strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong> - to produce sequencing libraries from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs. Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time. <span>The library preparation takes place in a </span><strong>single tube</strong><span>, increasing the efficiency tremendously. </span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span> - D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span> - D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex Unique Dual Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex Unique Dual Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended to mitigate errors introduced by read misassignment, including index hopping frequently observed with patterned flow cells such as Illumina’s NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
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<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
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<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM ≥5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
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<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R² > 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
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<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
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<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3’-end and primed with an oligo(dT) primer containing part of the ILMN 3’-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5’-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
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'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p> </p>
<p> </p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for <span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p> </p>
<p> </p>',
'label3' => 'Data analysis - Counting using MGcount',
'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select “stranded mode” in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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'name' => 'D-Plex Small RNA-seq Kit for Illumina',
'description' => '<div class="small-12 medium-12 large-12 columns" style="border: 3px solid #B02736; padding: 10px; margin: 10px;">
<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integration into numerous transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
</ul>
</div>
<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes two innovative <strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong> - to produce sequencing libraries from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs. Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time. <span>The library preparation takes place in a </span><strong>single tube</strong><span>, increasing the efficiency tremendously. </span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span> - D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span> - D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex Unique Dual Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex Unique Dual Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended to mitigate errors introduced by read misassignment, including index hopping frequently observed with patterned flow cells such as Illumina’s NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
'label1' => 'Characteristics and library prep. workflow ',
'info1' => '<div class="row">
<div class="small-12 columns">
<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM ≥5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R² > 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3’-end and primed with an oligo(dT) primer containing part of the ILMN 3’-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5’-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
</div>
</div>
<p><br /><br /></p>
<p></p>
<script async="" src="https://edge.fullstory.com/s/fs.js" crossorigin="anonymous"></script>
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'label2' => 'Data analysis',
'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p> </p>
<p> </p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for <span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p> </p>
<p> </p>',
'label3' => 'Data analysis - Counting using MGcount',
'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select “stranded mode” in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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View::_render() - CORE/Cake/View/View.php, line 933
View::render() - CORE/Cake/View/View.php, line 473
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<p><img src="https://www.diagenode.com/img/product/kits/figure-igv-microchip.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1:</strong> Integrative genomics viewer (IGV) visualization of ChIP-seq experiments using 50,000 of K562 cells.</p>
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<h2 style="text-align: center;"></h2>
<h2 style="text-align: center;">MicroChIP DiaPure columns after CUT&Tag</h2>
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<p><img src="https://www.diagenode.com/img/product/kits/figure-diapure-igv.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 2:</strong> Integrative genomics viewer (IGV) visualization of CUT&Tag experiments: MicroChIP DiaPure columns vs phenol-chloroform purification using the H3K27me3 antibody.</p>',
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'description' => '<div class="small-12 medium-12 large-12 columns" style="border: 3px solid #B02736; padding: 10px; margin: 10px;">
<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integration into numerous transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
</ul>
</div>
<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes two innovative <strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong> - to produce sequencing libraries from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs. Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time. <span>The library preparation takes place in a </span><strong>single tube</strong><span>, increasing the efficiency tremendously. </span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span> - D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span> - D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex Unique Dual Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex Unique Dual Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended to mitigate errors introduced by read misassignment, including index hopping frequently observed with patterned flow cells such as Illumina’s NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
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<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM ≥5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R² > 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3’-end and primed with an oligo(dT) primer containing part of the ILMN 3’-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5’-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
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<p><br /><br /></p>
<p></p>
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'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p> </p>
<p> </p>
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<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for <span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
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<p> </p>
<p> </p>',
'label3' => 'Data analysis - Counting using MGcount',
'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select “stranded mode” in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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'
$related = array(
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'antibody_id' => null,
'name' => 'D-Plex Small RNA-seq Kit for Illumina',
'description' => '<div class="small-12 medium-12 large-12 columns" style="border: 3px solid #B02736; padding: 10px; margin: 10px;">
<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integration into numerous transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
</ul>
</div>
<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes two innovative <strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong> - to produce sequencing libraries from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs. Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time. <span>The library preparation takes place in a </span><strong>single tube</strong><span>, increasing the efficiency tremendously. </span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span> - D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span> - D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex Unique Dual Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex Unique Dual Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended to mitigate errors introduced by read misassignment, including index hopping frequently observed with patterned flow cells such as Illumina’s NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
'label1' => 'Characteristics and library prep. workflow ',
'info1' => '<div class="row">
<div class="small-12 columns">
<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM ≥5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R² > 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3’-end and primed with an oligo(dT) primer containing part of the ILMN 3’-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5’-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
</div>
</div>
<p><br /><br /></p>
<p></p>
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'label2' => 'Data analysis',
'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p> </p>
<p> </p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for <span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p> </p>
<p> </p>',
'label3' => 'Data analysis - Counting using MGcount',
'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select “stranded mode” in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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'meta_title' => 'D-Plex Barcodes for MGI Sequencing - RNA Library Prep Kit - Set B | Diagenode ',
'meta_keywords' => 'RNA Library Prep Kit',
'meta_description' => 'Compatible with D-Plex Small RNA DNBSEQ kit - Barcodes for MGI sequencing - Multiplexing up to 48 samples - Suitable for ultra-low input (100 pg total RNA)',
'modified' => '2022-01-03 10:04:02',
'created' => '2020-12-18 11:31:06',
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'name' => 'MicroChIP DiaPure columns',
'description' => '<p><a href="https://www.diagenode.com/files/products/reagents/MicroChIP_DiaPure_manual.pdf"><img src="https://www.diagenode.com/img/buttons/bt-manual.png" /></a></p>
<p>Diagenode’s MicroChIP DiaPure columns have been optimized for the purification and elution of very low amounts of DNA. This rapid method has been validated for epigenetic applications like low input ChIP (e.g. using the True MicroChIP kit) and CUT&Tag (e.g. using Diagenode’s pA-Tn5), but is also compatible with many other applications. The DNA can be eluted at high concentrations in volumes down to 6 μl and it is suitable for any downstream application (e.g. NGS).</p>
<p>Benefits of the MicroChIP DiaPure columns:</p>
<ul>
<li>Optimized for the purification of very low DNA amounts</li>
<li>Fast and easy protocol</li>
<li>Non-toxic</li>
<li>Validated for ChIP and Cut&Tag</li>
</ul>',
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'info1' => '<h2 style="text-align: center;">MicroChIP DiaPure columns after ChIP</h2>
<p>Successful ChIP-seq results generated on 50,000 of K562 cells using True MicroChIP technology. ChIP has been performed accordingly to True MicroChIP protocol (Diagenode, Cat. No. C01010130), including DNA purification using the MicroChIP DiaPure columns. For the library preparation the MicroPlex Library Preparation Kit (Diagenode, Cat. No. C05010001) has been used. The below figure shows the peaks from ChIP-seq experiments using the following Diagenode antibodies: H3K4me1 (C15410194), H3K9/14ac (C15410200), H3K27ac (C15410196) and H3K36me3 (C15410192).</p>
<p><img src="https://www.diagenode.com/img/product/kits/figure-igv-microchip.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 1:</strong> Integrative genomics viewer (IGV) visualization of ChIP-seq experiments using 50,000 of K562 cells.</p>
<p></p>
<h2 style="text-align: center;"></h2>
<h2 style="text-align: center;">MicroChIP DiaPure columns after CUT&Tag</h2>
<p>Successful CUT&Tag results showing a low background with high region-specific enrichment has been generated using 50.000 of K562 cells, 1 µg of H3K27me3 antibody (Diagenode, Cat. No. C15410069) and proteinA-Tn5 (1:250) (Diagenode, Cat. No. C01070001). 1 µg of IgG (Diagenode, Cat. No. C15410206) was used as negative control. Samples were purified using the MicroChIP DiaPure columns or phenol-chloroform purification. The below figure presenst the comparison of two purification methods.</p>
<p><img src="https://www.diagenode.com/img/product/kits/figure-diapure-igv.png" style="display: block; margin-left: auto; margin-right: auto;" /></p>
<p><strong>Figure 2:</strong> Integrative genomics viewer (IGV) visualization of CUT&Tag experiments: MicroChIP DiaPure columns vs phenol-chloroform purification using the H3K27me3 antibody.</p>',
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'description' => '<div class="small-12 medium-12 large-12 columns" style="border: 3px solid #B02736; padding: 10px; margin: 10px;">
<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integration into numerous transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
</ul>
</div>
<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes two innovative <strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong> - to produce sequencing libraries from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs. Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time. <span>The library preparation takes place in a </span><strong>single tube</strong><span>, increasing the efficiency tremendously. </span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span> - D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span> - D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex Unique Dual Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex Unique Dual Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended to mitigate errors introduced by read misassignment, including index hopping frequently observed with patterned flow cells such as Illumina’s NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
'label1' => 'Characteristics and library prep. workflow ',
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<div class="small-12 columns">
<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM ≥5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R² > 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3’-end and primed with an oligo(dT) primer containing part of the ILMN 3’-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5’-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
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<p><br /><br /></p>
<p></p>
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'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p> </p>
<p> </p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for <span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p> </p>
<p> </p>',
'label3' => 'Data analysis - Counting using MGcount',
'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select “stranded mode” in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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'description' => '<div class="small-12 medium-12 large-12 columns" style="border: 3px solid #B02736; padding: 10px; margin: 10px;">
<h2>Product Features</h2>
<ul style="list-style-type: disc;">
<li>Ultra-low input capability, down to 10 pg for small RNAs and 100 pg for total RNA samples</li>
<li>High library complexity providing novel and diverse transcript detection</li>
<li>Versatile integration into numerous transcriptomic analysis workflow: ribosome profiling, CLIP-seq, RIP-seq and other</li>
<li>Improved quantification accuracy through the use of UMIs</li>
<li>Easy to use with minimal hands-on time: one day, one tube protocol</li>
</ul>
</div>
<p></p>
<p></p>
<center><em><a class="chip diahome button" href="https://www.diagenode.com/files/products/kits/MA-D-Plex.pdf" target="_blank" title="D-Plex Small RNA library preparation user manual"><strong>Download the manual</strong></a></em></center>
<p>D-Plex Small RNA-seq Library Prep Kit is a tool designed for the study of the <strong>small non-coding transcriptome</strong>. The kit is using the<a href="https://www.diagenode.com/en/pages/dplex" target="_blank"> D-Plex technology</a> to generate small RNA libraries for Illumina sequencing directly from total RNAs or enriched small RNAs.</p>
<p>The D-Plex technology utilizes two innovative <strong>ligation-free mechanisms</strong> - <strong>poly(A) tailing</strong> and <strong>template switching</strong> - to produce sequencing libraries from ultra-low input amounts, down to 10 pg for small RNAs and 100 pg for total RNAs. Combined with <strong>unique molecular identifiers</strong> (UMI), this complete solution ensures a <strong>realistic</strong> and <strong>accurate representation of diverse small RNA species</strong> (such as microRNAs, piRNAs, tRNAs, and siRNAs) with minimized quantitative bias.</p>
<p>D-Plex Small RNA-seq Kit offers a time saving protocol that can be completed within <strong>5 hours</strong> and requires minimal hands-on time. <span>The library preparation takes place in a </span><strong>single tube</strong><span>, increasing the efficiency tremendously. </span></p>
<p>D-Plex Small RNA-seq Kit includes all buffers and enzymes necessary for the library preparation. Specific D-Plex Indexes were designed and validated to fit the D-Plex technology and are available separately:</p>
<p><strong>For D-Plex UDI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-A" title="D-Plex UDI Module - Set A" target="_blank"><span>C05030021</span> - D-Plex Unique Dual Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-B" title="D-Plex UDI Module - Set B" target="_blank"><span>C05030022</span> - D-Plex Unique Dual Indexes for Illumina - Set B</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-C">C05030023 - D-Plex Unique Dual Indexes for Illumina - Set C</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Unique-Dual-Indexes-Set-D">C05030024 - D-Plex Unique Dual Indexes for Illumina - Set D</a></li>
</ul>
<p><span>The use of UDI is highly recommended to mitigate errors introduced by read misassignment, including index hopping frequently observed with patterned flow cells such as Illumina’s NovaSeq system.</span></p>
<p><strong>For D-Plex SI library construction:</strong></p>
<ul style="list-style-type: disc;">
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-A" title="D-Plex SI Module - Set A" target="_blank">C05030010 - D-Plex Single Indexes for Illumina - Set A</a></li>
<li><a href="https://www.diagenode.com/en/p/D-Plex-24-Single-Indexes-Set-B" title="D-Plex SI Module - Set B" target="_blank">C05030011 - D-Plex Single Indexes for Illumina - Set B</a></li>
</ul>
<p><strong>D-Plex is also available for MGI sequencing, check <a href="https://www.diagenode.com/en/p/d-plex-small-RNA-dnbseq-kit-x24" target="_blank">here</a>!</strong></p>
<p></p>
<p></p>
<p></p>
<center><strong>The D-Plex smRNA-seq is a versatile tool for a plethora of transciptomic analysis</strong></center>
<p></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/versatile-circle.png" /></center>
<p></p>
<p>With low-input capability, accuracy and ability to incorporate different transcript classes independent of chemical moieties, the strong D-Plex library-preparation method can be included in various analysis workflows (i.e., ribosome profiling, genome-wide mapping of protein: RNA binding sites).</p>
<p></p>
<p></p>',
'label1' => 'Characteristics and library prep. workflow ',
'info1' => '<div class="row">
<div class="small-12 columns">
<p><strong>High library diversity for ultra-low inputs</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-diversity-fig1.png" /></center></div>
<div class="small-12 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig2-captures.png" /></center></div>
</div>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>D-Plex smRNA-seq captures the smRNA complexity of the sample in a sensitive manner. A large number of features is detected for each biotype at a CPM ≥5, as shown above for different species.</p>
</div>
</div>
<p></p>
<p><strong>Accurate representation of the smRNA content of a sample</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-ratplasma.png" /></center></div>
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-miRNAdistribution.png" /></center></div>
</div>
<div class="row">
<div class="small-6 columns">
<p><strong>Accurate identification of PCR duplicates in low-input samples using unique molecular identifiers (UMIs).</strong><br />The UMI read deduplication that is embedded in the D-Plex construct is used to avoid over-estimation of transcripts by identifying clones generated during the PCR amplification of the library. Despite limiting starting RNA input, the UMI correction removed technical copies of transcripts, maintaining the initial sample abundance.</p>
</div>
<div class="small-6 columns">
<p>D-Plex (template switching) technology enables recovery of the initial miRNA distribution of the miRXplore Universal Reference (Miltenyi Biotech Inc., Cat. No. 130-093-521). In contrast, ligation-based kits display a strong distortion of the miRNA equimolar distribution initially present in the pool, indicating sample incorporation bias.</p>
</div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-foldchange.jpg" /></center></div>
<div class="small-6 columns"><strong>D-Plex smRNA-seq in association with the MGcount analysis correlates strongly (R² > 0.8) with the RT-qPCR analysis, which is considered the gold-standard for accuracy. </strong><br />The figures shows a fold-change accuracy of a panel of 20 different small-RNA (figure taken from MGcount publication - Hita et al., BMC bioinformatics, 23-39(2022).</div>
</div>
<p></p>
<p></p>
<p><strong>Maximize information from the regulatory transcriptome using D-Plex small RNA-seq kit and MGcount*</strong></p>
<div class="row">
<div class="small-6 columns"><center><img src="https://www.diagenode.com/img/product/kits/dplex/dplex-fig-multialignments.png" /></center></div>
<div class="small-6 columns">By analyzing D-Plex dataset with MGcount, more reads are kept during the analysis, which ultimately preserves biological complexity linked to ncRNA expression without decreasing the accuracy of detection. <br /><span style="line-height: 1em;"><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></span></div>
</div>
<p></p>
<p></p>
<div class="row">
<div class="small-12 columns">
<p>The D-Plex technology uses two innovative ligation-free mechanisms, <strong>poly(A) tailing and template switching</strong>, to produce sequencing libraries from ultra-low input amounts.</p>
</div>
</div>
<div class="row" style="background-color: #f5f5f5;">
<div class="small-12 columns"><br />
<p><strong>WORKFLOW</strong></p>
<center><img src="https://www.diagenode.com/img/product/kits/dplex/FL-Image-Workflow.jpg" width="50%" /></center></div>
<div class="small-12 columns">
<p style="text-align: justify; padding: 15px;"><br />RNA molecules are polyadenylated at the 3’-end and primed with an oligo(dT) primer containing part of the ILMN 3’-adapter sequence. The addition of a template-switching oligonucleotide during cDNA synthesis enables fusion of part of the ILMN 5’-adapter during reverse transcription. After PCR, the library comprises double stranded DNA constructs that are ready for sequencing.</p>
</div>
</div>
<p><br /><br /></p>
<p></p>
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'info2' => '<p>A specific bioinformatics pipeline has been developed to process the special sequences present in the D-Plex construct, namely the UMI, the A-tail, and the template switch motif. All guidelines and free softwares are shared in the user manual. Subject to the compatibility of D-Plex constructs, other specific pipelines can be used.</p>
<p><img src="https://www.diagenode.com/img/product/kits/dplex/bioinfoPipe.png" alt="small RNA sequencing bioinformatics pipeline" caption="false" width="925" height="196" /></p>
<p>Need help for your bioinformatics analysis of miRNA?</p>
<p></p>
<div class="small-12 medium-3 large-3 columns"><center><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"><img src="https://www.diagenode.com/img/product/kits/dplex/miRMaster_logo.png" /></a></center>
<p> </p>
<p> </p>
</div>
<div class="small-12 medium-9 large-9 columns">
<p>Diagenode has collaborated with <strong>Andreas Keller</strong> and <strong>Tobias Fehlmann</strong> to develop a new bioinformatics pipeline for <span>the <strong>prediction of novel miRNAs</strong>.</span><br /><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank"></a></p>
<ul>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster2">miRMaster 2</a></li>
<li style="text-align: justify;"><a href="https://ccb-compute.cs.uni-saarland.de/mirmaster" target="_blank">miRMaster</a></li>
</ul>
</div>
<p> </p>
<p> </p>',
'label3' => 'Data analysis - Counting using MGcount',
'info3' => '<p>The counting or expression level calculation is the last step of the processing to generate an expression level matrix. We recommend using MGcount*, a counting tool developed at Diagenode with a suitable annotations file that include the small RNA transcripts that are object of study. MGcount, built on top of featureCounts, employs a flexible quantification approach to deal with datasets containing multiple RNA biotypes such as D-plex libraries. Non-coding RNAs varying in length, biogenesis, and function, may overlap in a genomic region, and are sometimes present in the genome with a high copy number. Consequently, reads may align equally well to more than one position in the reference genome or/and align to a position where more than one annotated transcript is located. MGcount employs two strategies to quantify these reads. Firstly, it assigns reads in rounds prioritizing small-RNAs over long-RNAs ensuring the unbiased read attribution to intergenic and intragenic small RNAs while preventing host-genes transcription over-estimation. Secondly, MGcount collapses loci where reads consistently multi-map into communities of loci with a graph-based approach. The resultant communities are groups of biologically related loci with nearly identical sequence. Subsequently, quantification of reads is performed at the loci-community level, reducing multi-alignments ambiguity at individual locus. Ultimately, this strategy maximizes the transcriptome information analysed and improves the interrogation of non-coding RNAs. MGcount software repository provides annotation files for A. thaliana, H. sapiens, M. musculus and C. elegans. The required input files for MGcount are a .txt file listing the paths to the alignment input files (.bam format) and the annotations file (.gtf format). The output directory path has to be provided as an input as well.</p>
<p><strong>Example command:</strong></p>
<p style="background-color: #f0f0f0;">MGcount -T 2 --gtf Homo_sapiens.GRCh38.gtf --outdir outputs --bam_infiles input_bamfilenames.txt</p>
<p>MGcount provides the choice to enable/disable the quantification of all RNA biotypes included in the annotation file in the form of "communities" as optional parameters for small-RNA (--ml_flag_small) and long-RNA (--ml_flag_long). Both are enabled by default. The main output of MGcount is the count_matrix.csv file containing an expression matrix that can be imported to R or any other software for downstream analyses.<br />A full user guide for MGCount is available here: <a href="https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html">https://filedn.com/lTnUWxFTA93JTyX3Hvbdn2h/mgcount/UserGuide.html</a>.</p>
<p>Other standard counting tools such as featureCounts or HTSeq-counts can also be used alternatively. Given the high complexity of D-Plex libraries, we recommend having a clear understanding of the scientific question and the goal of the project before proceeding to the choice of the counting method as this will strongly impact downstream analyses. Diagenode provides bioinformatics support as a service (please, contact us if you need help with data analysis).</p>
<p>Notice that D-Plex produces forward-stranded data. Stranded libraries have the benefit that reads map to the genome strand where they were originated from. Therefore, when estimating transcript expression, reads aligned to the forward strand should be assigned only to transcript features in the forward strand whereas reads aligned to the reverse strand should be assigned only to transcript features in the reverse strand. For this, make sure you select “stranded mode” in any tool of choice. Stranded mode is selected by default in MGcount.</p>
<p><em><small>*Hita, A., Brocart, G., Fernandez, A. et al. MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts. BMC Bioinformatics 23, 39 (2022). <a href="https://doi.org/10.1186/s12859-021-04544-3">https://doi.org/10.1186/s12859-021-04544-3</a></small></em></p>',
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