Integrative pathway enrichment analysis of multivariate omics data
Integrative pathway enrichment analysis of multivariate omics data
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DOI：
10.1038/s41467-019-13983-9
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发表时间：
2020-02-05
影响因子：
16.6
通讯作者：
Reimand, Juri
中科院分区：
文献类型：
--
作者：
Paczkowska, Marta;Barenboim, Jonathan;Reimand, Juri
多组学数据集代表了分子生物学中心法则的不同方面。这种高维分子谱对数据解释和假设生成提出了挑战。ActivePathways是一种综合方法，使用统计数据融合在多个数据集上发现显著丰富的途径，合理化贡献证据并突出相关基因。作为ICGC/TCGA泛癌症全基因组分析（PCAWG）联盟的一部分，该联盟汇总了来自38种肿瘤类型的2658种癌症的全基因组测序数据，我们整合了具有编码和非编码突变的基因，并揭示了频繁突变的途径和其他具有罕见突变的癌症基因。我们还通过整合1780例乳腺癌的基因组和转录组学特征分析了预后分子通路，并强调了与免疫应答和抗凋亡信号的相关性。整合ChIP-seq和RNA-seq数据，用于在正常人体组织中识别组织再生和干细胞调节的过程。ActivePathways是一种多功能方法，通过整合多个分子数据集和途径注释，提高了对健康和疾病中细胞组织的系统水平理解。
Multi-omics datasets represent distinct aspects of the central dogma of molecular biology. Such high-dimensional molecular profiles pose challenges to data interpretation and hypothesis generation. ActivePathways is an integrative method that discovers significantly enriched pathways across multiple datasets using statistical data fusion, rationalizes contributing evidence and highlights associated genes. As part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we integrated genes with coding and non-coding mutations and revealed frequently mutated pathways and additional cancer genes with infrequent mutations. We also analyzed prognostic molecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highlighted associations with immune response and anti-apoptotic signaling. Integration of ChIP-seq and RNA-seq data for master regulators of the Hippo pathway across normal human tissues identified processes of tissue regeneration and stem cell regulation. ActivePathways is a versatile method that improves systems-level understanding of cellular organization in health and disease through integration of multiple molecular datasets and pathway annotations.