Integrative pathway enrichment analysis of multivariate omics data
| Autor: | Paczkowska M., Barenboim J., Sintupisut N., Fox N. S., Zhu H., Abd-Rabbo D., Mee M. W., Boutros P. C., Abascal F., Amin S. B., Bader G. D., Beroukhim R., Bertl J., Boroevich K. A., Brunak S., Campbell P. J., Carlevaro-Fita J., Chakravarty D., Chan C. W. Y., Chen K., Choi J. K., Deu-Pons J., Dhingra P., Diamanti K., Feuerbach L., Fink J. L., Fonseca N. A., Frigola J., Gambacorti Passerini C., Garsed D. W., Gerstein M., Getz G., Gonzalez-Perez A., Guo Q., Gut I. G., Haan D., Hamilton M. P., Haradhvala N. J., Harmanci A. O., Helmy M., Herrmann C., Hess J. M., Hobolth A., Hodzic E., Hong C., Hornshoj H., Isaev K., Izarzugaza J. M. G., Johnson R., Johnson T. A., Juul M., Juul R. I., Kahles A., Kahraman A., Kellis M., Khurana E., Kim J., Kim J. K., Kim Y., Komorowski J., Korbel J. O., Kumar S., Lanzos A., Lawrence M. S., Lee D., Lehmann K. -V., Li S., Li X., Lin Z., Liu E. M., Lochovsky L., Lou S., Madsen T., Marchal K., Martincorena I., Martinez-Fundichely A., Maruvka Y. E., McGillivray P. D., Meyerson W., Muinos F., Mularoni L., Nakagawa H., Nielsen M. M., Park K., Pedersen J. S., Pich O., Pons T., Pulido-Tamayo S., Raphael B. J., Reyes-Salazar I., Reyna M. A., Rheinbay E., Rubin M. A., Rubio-Perez C., Sabarinathan R., Sahinalp S. C., Saksena G., Salichos L., Sander C., Schumacher S. E., Shackleton M., Shapira O., Shen C., Shrestha R., Shuai S., Sidiropoulos N., Sieverling L., Sinnott-Armstrong N., Stein L. D., Stuart J. M., Tamborero D., Tiao G., Tsunoda T., Umer H. M., Uuskula-Reimand L., Valencia A., Vazquez M., Verbeke L. P. C., Wadelius C., Wadi L., Wang J., Warrell J., Waszak S. M., Weischenfeldt J., Wheeler D. A., Wu G., Yu J., Zhang J., Zhang X., Zhang Y., Zhao Z., Zou L., von Mering C., Reimand J. |
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| Přispěvatelé: | Boutros, Paul C [0000-0003-0553-7520], Reimand, Jüri [0000-0002-2299-2309], Apollo - University of Cambridge Repository, Paczkowska, M, Barenboim, J, Sintupisut, N, Fox, N, Zhu, H, Abd-Rabbo, D, Mee, M, Boutros, P, Abascal, F, Amin, S, Bader, G, Beroukhim, R, Bertl, J, Boroevich, K, Brunak, S, Campbell, P, Carlevaro-Fita, J, Chakravarty, D, Chan, C, Chen, K, Choi, J, Deu-Pons, J, Dhingra, P, Diamanti, K, Feuerbach, L, Fink, J, Fonseca, N, Frigola, J, Gambacorti Passerini, C, Garsed, D, Gerstein, M, Getz, G, Gonzalez-Perez, A, Guo, Q, Gut, I, Haan, D, Hamilton, M, Haradhvala, N, Harmanci, A, Helmy, M, Herrmann, C, Hess, J, Hobolth, A, Hodzic, E, Hong, C, Hornshoj, H, Isaev, K, Izarzugaza, J, Johnson, R, Johnson, T, Juul, M, Juul, R, Kahles, A, Kahraman, A, Kellis, M, Khurana, E, Kim, J, Kim, Y, Komorowski, J, Korbel, J, Kumar, S, Lanzos, A, Lawrence, M, Lee, D, Lehmann, K, Li, S, Li, X, Lin, Z, Liu, E, Lochovsky, L, Lou, S, Madsen, T, Marchal, K, Martincorena, I, Martinez-Fundichely, A, Maruvka, Y, Mcgillivray, P, Meyerson, W, Muinos, F, Mularoni, L, Nakagawa, H, Nielsen, M, Park, K, Pedersen, J, Pich, O, Pons, T, Pulido-Tamayo, S, Raphael, B, Reyes-Salazar, I, Reyna, M, Rheinbay, E, Rubin, M, Rubio-Perez, C, Sabarinathan, R, Sahinalp, S, Saksena, G, Salichos, L, Sander, C, Schumacher, S, Shackleton, M, Shapira, O, Shen, C, Shrestha, R, Shuai, S, Sidiropoulos, N, Sieverling, L, Sinnott-Armstrong, N, Stein, L, Stuart, J, Tamborero, D, Tiao, G, Tsunoda, T, Umer, H, Uuskula-Reimand, L, Valencia, A, Vazquez, M, Verbeke, L, Wadelius, C, Wadi, L, Wang, J, Warrell, J, Waszak, S, Weischenfeldt, J, Wheeler, D, Wu, G, Yu, J, Zhang, J, Zhang, X, Zhang, Y, Zhao, Z, Zou, L, von Mering, C, Reimand, J |
| Rok vydání: | 2020 |
| Předmět: |
0301 basic medicine
HOMEOSTASIS Databases Factual Messenger Medizin Gene Dosage General Physics and Astronomy RNA-Seq Apoptosis Disease Genome Transcriptome 0302 clinical medicine PCAWG Drivers and Functional Interpretation Working Group Neoplasms BINDING Cancer genomics Medicine and Health Sciences 2.1 Biological and endogenous factors Gene Regulatory Networks NETWORK Aetiology Càncer lcsh:Science Multidisciplinary Women's cancers Radboud Institute for Molecular Life Sciences [Radboudumc 17] Genomics ATLAS Prognosis CANCER 3. Good health Women's cancers Radboud Institute for Health Sciences [Radboudumc 17] 030220 oncology & carcinogenesis Data integration Female YAP Sequence Analysis Metabolic Networks and Pathways Biotechnology Signal Transduction genome sequencing breast cancers RNA-seq whole-genome sequencing (WGS) data multi-omics pathway Chromatin Immunoprecipitation Science 610 Medicine & health Breast Neoplasms Computational biology Biology Adenocarcinoma Protein Serine-Threonine Kinases Article General Biochemistry Genetics and Molecular Biology DNA sequencing Databases 03 medical and health sciences Breast Cancer Genetics medicine Humans Hippo Signaling Pathway RNA Messenger Gene Factual SIGNATURES Biologia molecular HIPPO PATHWAY MUTATIONS Sequence Analysis RNA Gene Expression Profiling Human Genome Cancer Biology and Life Sciences PCAWG Consortium Computational Biology General Chemistry Stem Cell Research medicine.disease Omics Genòmica Good Health and Well Being 030104 developmental biology Mutation RNA Gene ontology lcsh:Q Genètica |
| Zdroj: | Nature Communications, 11, 1 Paczkowska, M, Barenboim, J, Sintupisut, N, Fox, N S, Zhu, H, Abd-Rabbo, D, Mee, M W, Boutros, P C, Abascal, F, Amin, S B, Bader, G D, Beroukhim, R, Bertl, J, Boroevich, K A, Brunak, S, Campbell, P J, Carlevaro-Fita, J, Chakravarty, D, Chan, C W Y, Chen, K, Choi, J K, Deu-Pons, J, Dhingra, P, Diamanti, K, Feuerbach, L, Fink, J L, Fonseca, N A, Frigola, J, Gambacorti-Passerini, C, Garsed, D W, Gerstein, M, Getz, G, Gonzalez-Perez, A, Guo, Q, Gut, I G, Haan, D, Hamilton, M P, Haradhvala, N J, Harmanci, A O, Helmy, M, Herrmann, C, Hess, J M, Hobolth, A, Hodzic, E, Hong, C, Hornshøj, H, Nielsen, M M, Pedersen, J S, Sidiropoulos, N & Weischenfeldt, J 2020, ' Integrative pathway enrichment analysis of multivariate omics data ', Nature Communications, vol. 11, no. 1, 735 . https://doi.org/10.1038/s41467-019-13983-9 Nature Communications, 11 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 2020, ' Integrative pathway enrichment analysis of multivariate omics data ', Nature Communications, vol. 11, no. 1, 735 . https://doi.org/10.1038/s41467-019-13983-9 Nature communications, vol 11, iss 1 Nature Communications, Vol 11, Iss 1, Pp 1-16 (2020) NATURE COMMUNICATIONS Nature Communications, 11 (1) Nature Communications Paczkowska, Marta; Barenboim, Jonathan; Sintupisut, Nardnisa; Fox, Natalie S; Zhu, Helen; Abd-Rabbo, Diala; Mee, Miles W; Boutros, Paul C; Reimand, Jüri (2020). Integrative pathway enrichment analysis of multivariate omics data. Nature communications, 11(1), p. 735. 10.1038/s41467-019-13983-9 |
| ISSN: | 2041-1723 |
| DOI: | 10.1038/s41467-019-13983-9 |
| Popis: | 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. Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery. |
| Databáze: | OpenAIRE |
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