Total RNA sequencing (RNA-Seq) detects both coding and noncoding RNAs and is typically used to measure gene and transcript abundance as well as to identify novel components of the transcriptome. Messenger RNA-Seq focuses on the quantification of gene expression, the identification of unknown transcripts, the discovery of alternative splicing and gene fusion events. And finally, small non-coding RNA sequencing (sncRNA-Seq) will detect small (<100 nucleotides long) RNAs that operate as key regulators in cellular processes.
What do we provide with the analysis?
This analysis provides information for either genes or isoforms with their expression levels.
Standard Analysis
Summary statistics (total sequenced reads, total mapping reads, uniquely aligned reads, PCR duplicates, number of genes detected, average read density per gene, number of highly expressed genes, etc.)
Trimmed and filtered reads in fastQ files after sequencing QC
BAM sorted files from alignment to reference genome or transcriptome (indexed bam files and bigwig files included)
Matrix with expression abundance obtained with specialized quantification tool MGCount (software developed by Diagenode). A table of MG communities linking each original feature in the GTF file with the resultant count matrix and metadata feature identifiers.
Advanced Analysis
Comparative analysis (also called differential analysis) aimed at finding differentially expressed genes (DEGs) between two groups of samples
Functional gene annotation
Gene ontology enrichment analysis on DEGs
Pathway enrichment analysis on DEGs (KEGG or DOSE for human samples)
MGcount: Diagenode has developed a bioinformatics software for counting whole-transcriptome RNA-seq reads from one or more input alignment files. It is specially designed to incorporate multi-mapping and multi-overlapping reads in the quantification using a flexible methodology that is compatible with any biotype. At the end of its execution, it produces a count matrix, compatible with any downstream analysis.
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MGcount: a total RNA-seq quantification tool to address multi-mappingand multi-overlapping alignments ambiguity in non-coding transcripts Hita Andrea, Brocart Gilles, Fernandez Ana, Rehmsmeier Marc, Alemany Anna, Schvartzman Sol Background Total-RNA sequencing (total-RNA-seq) allows the simultaneous study of both the coding and the non-coding transcriptome. Yet, computational pipelines have traditionally focused on particular biotypes, making assumptions that are not fullfilled by total-RNA-seq datasets. Transcripts from distinct RNA biotyp...