TY - JOUR
T1 - Integrative pathway enrichment analysis of multivariate omics data
AU - PCAWG Drivers and Functional Interpretation Working Group
AU - PCAWG Consortium
AU - Paczkowska, Marta
AU - Barenboim, Jonathan
AU - Sintupisut, Nardnisa
AU - Fox, Natalie S.
AU - Zhu, Helen
AU - Abd-Rabbo, Diala
AU - Mee, Miles W.
AU - Boutros, Paul C.
AU - Abascal, Federico
AU - Amin, Samirkumar B.
AU - Bader, Gary D.
AU - Beroukhim, Rameen
AU - Bertl, Johanna
AU - Boroevich, Keith A.
AU - Brunak, Søren
AU - Campbell, Peter J.
AU - Carlevaro-Fita, Joana
AU - Chakravarty, Dimple
AU - Chan, Calvin Wing Yiu
AU - Chen, Ken
AU - Choi, Jung Kyoon
AU - Deu-Pons, Jordi
AU - Dhingra, Priyanka
AU - Diamanti, Klev
AU - Feuerbach, Lars
AU - Fink, J. Lynn
AU - Fonseca, Nuno A.
AU - Frigola, Joan
AU - Gambacorti-Passerini, Carlo
AU - Garsed, Dale W.
AU - Gerstein, Mark
AU - Getz, Gad
AU - Gonzalez-Perez, Abel
AU - Guo, Qianyun
AU - Gut, Ivo G.
AU - Haan, David
AU - Hamilton, Mark P.
AU - Haradhvala, Nicholas J.
AU - Harmanci, Arif O.
AU - Helmy, Mohamed
AU - Herrmann, Carl
AU - Hess, Julian M.
AU - Hobolth, Asger
AU - Hodzic, Ermin
AU - Hong, Chen
AU - Hornshøj, Henrik
AU - Isaev, Keren
AU - Wang, Jiayin
AU - Yang, Huanming
AU - Ye, Kai
N1 - Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12/1
Y1 - 2020/12/1
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85079073313
U2 - 10.1038/s41467-019-13983-9
DO - 10.1038/s41467-019-13983-9
M3 - 文章
C2 - 32024846
AN - SCOPUS:85079073313
SN - 2041-1723
VL - 11
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 735
ER -
SDG 3 Good Health and Well-being