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進行中または神経変性のガンや慢性疾患などの病理学的過程などで観察される表現型の変化をよりよく理解するために、複数のエピゲノム技術を組み合わせる必要性が数多くの研究で証明されています。
癌細胞で観察される表現型の変化は、DNAメチル化とクロマチン修飾パターンの両方の変化と強く関連していて、遺伝子発現は、DNAメチル化とクロマチンダイナミクスによって強く制御されています。一般的に特定のタンパク質が調節する遺伝子を発見するために、 クロマチン修飾に関する結合部位とトランスクリプトームデータが統合されます。 トランスクリプトミクスデータをオープンクロマチン領域と統合することで、遺伝子調節パターンの正確な評価を可能にします。メチル化プロファイルは、他のエピゲノミクスまたはトランスクリプトミクス測定と統合的に分析することがで、遺伝子の過剰発現または過少発現によるメチル化の役割を明らかにします。さまざまな「オミクス」データが利用可能であるからこそ、複数のエピゲノム技術を組み合わせる事が推奨されています。
この解析は様々な線形数学モデルを調査し、2セットのオミクスデータ間の関係を推定します。
![]() How to properly cite this product in your workDiagenode strongly recommends using this: Integrative Analysis (Diagenode Cat# G02500000). Click here to copy to clipboard. Using our products in your publication? Let us know! |
Notice (8): Undefined variable: solution_of_interest [APP/View/Products/view.ctp, line 755]Code Context<!-- BEGIN: REQUEST_FORM MODAL -->
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$viewFile = '/home/website-server/www/app/View/Products/view.ctp' $dataForView = array( 'language' => 'jp', 'meta_keywords' => '', 'meta_description' => '', 'meta_title' => '', 'product' => array( 'Product' => array( 'id' => '3063', 'antibody_id' => null, 'name' => 'Integrative Analysis', 'description' => '<div class="extra-spaced"> <p>進行中または神経変性のガンや慢性疾患などの病理学的過程などで観察される表現型の変化をよりよく理解するために、複数のエピゲノム技術を組み合わせる必要性が数多くの研究で証明されています。</p> <p>癌細胞で観察される表現型の変化は、DNAメチル化とクロマチン修飾パターンの両方の変化と強く関連していて、遺伝子発現は、DNAメチル化とクロマチンダイナミクスによって強く制御されています。一般的に特定のタンパク質が調節する遺伝子を発見するために、 クロマチン修飾に関する結合部位とトランスクリプトームデータが統合されます。 トランスクリプトミクスデータをオープンクロマチン領域と統合することで、遺伝子調節パターンの正確な評価を可能にします。メチル化プロファイルは、他のエピゲノミクスまたはトランスクリプトミクス測定と統合的に分析することがで、遺伝子の過剰発現または過少発現によるメチル化の役割を明らかにします。さまざまな「オミクス」データが利用可能であるからこそ、複数のエピゲノム技術を組み合わせる事が推奨されています。</p> </div> <h2>どのような種類のデータを組み合わせることができますか?</h2> <ul style="list-style-type: circle;"> <li>ChIP-Seq with methylation</li> <li>ATAC-Seq with methylation</li> <li>mRNA-Seq with methylation data</li> <li>sncRNA-Seq with ChIP-Seq or ATAC-Seq</li> <li>mRNA-Seq with ChIP-Seq or ATAC-Seq</li> <li>...and more</li> </ul> <p>この解析は様々な線形数学モデルを調査し、2セットのオミクスデータ間の関係を推定します。</p> <h3 class="diacol" style="font-weight: 100;">完全な解析</h3> <ul style="list-style-type: circle;"> <li>Summary statistics for the different technologies used</li> <li>Trimmed and filtered reads in fastQ files after sequencing QC</li> <li>BAM sorted files from alignment to reference genome or transcriptome (indexed bam files and bigwig files included)</li> <li>Outcome of interest:</li> <ul> <li>List of peaks with their enrichment level (ChIP-Seq, ATAC-Seq, MeDIP-Seq)</li> <li>List of CpGs with their methylation percentage (WGBS, RRBS, EPIC, BSAS)</li> <li>Matrix with expression abundance estimation (total, messenger and small non-coding RNA)</li> </ul> <li>Comparative analysis aimed at finding differential responses between two groups of samples</li> <li>Functional gene annotation on features with differential responses</li> <li>Integration of two sets of omics data - linear regression</li> <li>Gene ontology enrichment analysis of correlated features</li> </ul>', 'label1' => '', 'info1' => '', 'label2' => '', 'info2' => '', 'label3' => '', 'info3' => '', 'format' => '', 'catalog_number' => 'G02500000', 'old_catalog_number' => '', 'sf_code' => '', 'type' => 'ACC', 'search_order' => '', 'price_EUR' => '/', 'price_USD' => '/', 'price_GBP' => '/', 'price_JPY' => '42800', 'price_CNY' => '/', 'price_AUD' => '/', 'country' => 'ALL', 'except_countries' => 'None', 'quote' => true, 'in_stock' => false, 'featured' => true, 'no_promo' => false, 'online' => true, 'master' => true, 'last_datasheet_update' => '', 'slug' => 'integrative-analysis', 'meta_title' => '', 'meta_keywords' => '', 'meta_description' => '', 'modified' => '2021-02-22 10:56:17', 'created' => '2020-03-26 16:18:39', 'locale' => 'jpn' ), 'Antibody' => array( 'host' => '*****', 'id' => null, 'name' => null, 'description' => null, 'clonality' => null, 'isotype' => null, 'lot' => null, 'concentration' => null, 'reactivity' => null, 'type' => null, 'purity' => null, 'classification' => null, 'application_table' => null, 'storage_conditions' => null, 'storage_buffer' => null, 'precautions' => null, 'uniprot_acc' => null, 'slug' => null, 'meta_keywords' => null, 'meta_description' => null, 'modified' => null, 'created' => null, 'select_label' => null ), 'Slave' => array(), 'Group' => array(), 'Related' => array(), 'Application' => array(), 'Category' => array( (int) 0 => array( [maximum depth reached] ) ), 'Document' => array(), 'Feature' => array(), 'Image' => array(), 'Promotion' => array(), 'Protocol' => array(), 'Publication' => array(), 'Testimonial' => array(), 'Area' => array(), 'SafetySheet' => array() ) ) $language = 'jp' $meta_keywords = '' $meta_description = '' $meta_title = '' $product = array( 'Product' => array( 'id' => '3063', 'antibody_id' => null, 'name' => 'Integrative Analysis', 'description' => '<div class="extra-spaced"> <p>進行中または神経変性のガンや慢性疾患などの病理学的過程などで観察される表現型の変化をよりよく理解するために、複数のエピゲノム技術を組み合わせる必要性が数多くの研究で証明されています。</p> <p>癌細胞で観察される表現型の変化は、DNAメチル化とクロマチン修飾パターンの両方の変化と強く関連していて、遺伝子発現は、DNAメチル化とクロマチンダイナミクスによって強く制御されています。一般的に特定のタンパク質が調節する遺伝子を発見するために、 クロマチン修飾に関する結合部位とトランスクリプトームデータが統合されます。 トランスクリプトミクスデータをオープンクロマチン領域と統合することで、遺伝子調節パターンの正確な評価を可能にします。メチル化プロファイルは、他のエピゲノミクスまたはトランスクリプトミクス測定と統合的に分析することがで、遺伝子の過剰発現または過少発現によるメチル化の役割を明らかにします。さまざまな「オミクス」データが利用可能であるからこそ、複数のエピゲノム技術を組み合わせる事が推奨されています。</p> </div> <h2>どのような種類のデータを組み合わせることができますか?</h2> <ul style="list-style-type: circle;"> <li>ChIP-Seq with methylation</li> <li>ATAC-Seq with methylation</li> <li>mRNA-Seq with methylation data</li> <li>sncRNA-Seq with ChIP-Seq or ATAC-Seq</li> <li>mRNA-Seq with ChIP-Seq or ATAC-Seq</li> <li>...and more</li> </ul> <p>この解析は様々な線形数学モデルを調査し、2セットのオミクスデータ間の関係を推定します。</p> <h3 class="diacol" style="font-weight: 100;">完全な解析</h3> <ul style="list-style-type: circle;"> <li>Summary statistics for the different technologies used</li> <li>Trimmed and filtered reads in fastQ files after sequencing QC</li> <li>BAM sorted files from alignment to reference genome or transcriptome (indexed bam files and bigwig files included)</li> <li>Outcome of interest:</li> <ul> <li>List of peaks with their enrichment level (ChIP-Seq, ATAC-Seq, MeDIP-Seq)</li> <li>List of CpGs with their methylation percentage (WGBS, RRBS, EPIC, BSAS)</li> <li>Matrix with expression abundance estimation (total, messenger and small non-coding RNA)</li> </ul> <li>Comparative analysis aimed at finding differential responses between two groups of samples</li> <li>Functional gene annotation on features with differential responses</li> <li>Integration of two sets of omics data - linear regression</li> <li>Gene ontology enrichment analysis of correlated features</li> </ul>', 'label1' => '', 'info1' => '', 'label2' => '', 'info2' => '', 'label3' => '', 'info3' => '', 'format' => '', 'catalog_number' => 'G02500000', 'old_catalog_number' => '', 'sf_code' => '', 'type' => 'ACC', 'search_order' => '', 'price_EUR' => '/', 'price_USD' => '/', 'price_GBP' => '/', 'price_JPY' => '42800', 'price_CNY' => '/', 'price_AUD' => '/', 'country' => 'ALL', 'except_countries' => 'None', 'quote' => true, 'in_stock' => false, 'featured' => true, 'no_promo' => false, 'online' => true, 'master' => true, 'last_datasheet_update' => '', 'slug' => 'integrative-analysis', 'meta_title' => '', 'meta_keywords' => '', 'meta_description' => '', 'modified' => '2021-02-22 10:56:17', 'created' => '2020-03-26 16:18:39', 'locale' => 'jpn' ), 'Antibody' => array( 'host' => '*****', 'id' => null, 'name' => null, 'description' => null, 'clonality' => null, 'isotype' => null, 'lot' => null, 'concentration' => null, 'reactivity' => null, 'type' => null, 'purity' => null, 'classification' => null, 'application_table' => null, 'storage_conditions' => null, 'storage_buffer' => null, 'precautions' => null, 'uniprot_acc' => null, 'slug' => null, 'meta_keywords' => null, 'meta_description' => null, 'modified' => null, 'created' => null, 'select_label' => null ), 'Slave' => array(), 'Group' => array(), 'Related' => array(), 'Application' => array(), 'Category' => array( (int) 0 => array( 'id' => '140', 'position' => '0', 'parent_id' => null, 'name' => 'Epigenomics Data Analysis Service', 'description' => '<div class="row"> <div class="small-12 medium-12 large-12 columns"> <div class="extra-spaced"><iframe width="560" height="315" src="https://www.youtube.com/embed/Ro5AOX_348M" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="allowfullscreen"></iframe></div> </div> </div> <div class="extra-spaced"> <p>Epigenomic Services at Diagenode offers data analysis solutions for different application areas. 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Notice (8): Undefined variable: header [APP/View/Products/view.ctp, line 755]Code Context<!-- BEGIN: REQUEST_FORM MODAL -->
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