Integrative pathway enrichment analysis of multivariate omics data Journal Article


Authors: Paczkowska, M.; Barenboim, J.; Sintupisut, N.; Fox, N. S.; Zhu, H.; Abd-Rabbo, D.; Mee, M. W.; Boutros, P. C.; PCAWG Drivers and Functional Interpretation Working Group; Reimand, J.; & PCAWG Consortium
Contributors: Kahles, A.; Lehmann, K. V.; Liu, E. M.; Sander, C.; Abeshouse, A.; Al-Ahmadie, H.; Armenia, J.; Chen, H. W.; Davidson, N. R.; Gao, J.; Ghossein, R.; Giri, D. D.; Gundem, G.; Heins, Z.; Huse, J.; Iacobuzio-Donahue, C. A.; King, T. A.; Kundra, R.; Levine, D. A.; Ochoa, A.; Pastore, A.; Rätsch, G.; Reis-Filho, J.; Reuter, V.; Roehrl, M. H. A.; Sanchez-Vega, F.; Schultz, N.; Senbabaoglu, Y.; Singer, S.; Socci, N. D.; Stark, S. G.; Yellapantula, V. D.; Zhang, H.
Article Title: Integrative pathway enrichment analysis of multivariate omics data
Abstract: 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. © 2020, The Author(s).
Keywords: gene expression; molecular analysis; genomics; multivariate analysis; data set; cancer
Journal Title: Nature Communications
Volume: 11
ISSN: 2041-1723
Publisher: Nature Publishing Group  
Date Published: 2020-02-05
Start Page: 735
Language: English
DOI: 10.1038/s41467-019-13983-9
PUBMED: 32024846
PROVIDER: scopus
PMCID: PMC7002665
DOI/URL:
Notes: Article -- Erratum issued, see DOI: 10.1038/s41467-022-32342-9 -- Export Date: 2 March 2020 -- Source: Scopus
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  1. Ronald A Ghossein
    482 Ghossein
  2. Dilip D Giri
    184 Giri
  3. Douglas A Levine
    380 Levine
  4. Tari King
    186 King
  5. Samuel Singer
    337 Singer
  6. Jason T Huse
    143 Huse
  7. Nicholas D Socci
    266 Socci
  8. Chris Sander
    210 Sander
  9. Victor Reuter
    1228 Reuter
  10. Jianjiong Gao
    132 Gao
  11. Nikolaus D Schultz
    486 Schultz
  12. Gunnar Ratsch
    68 Ratsch
  13. Andre Kahles
    31 Kahles
  14. Hsiao-Wei Chen
    30 Chen
  15. Kjong Van Stephan Fritz Lehmann
    22 Lehmann
  16. Stefan G Stark
    17 Stark
  17. Michael H Roehrl
    127 Roehrl
  18. Alessandro   Pastore
    55 Pastore
  19. Joshua   Armenia
    56 Armenia
  20. Zachary Joseph Heins
    22 Heins
  21. Ritika   Kundra
    88 Kundra
  22. Hongxin Zhang
    47 Zhang
  23. Angelica Ochoa
    30 Ochoa
  24. Gunes Gundem
    56 Gundem
  25. Minwei Liu
    24 Liu