Zodiac

A Comprehensive Depiction of Genetic Interactions in Cancer by Integrating TCGA Data

Yitan Zhu, Yanxun Xu, Donald L. Helseth, Kamalakar Gulukota, Shengjie Yang, Lorenzo Luigi Pesce, Riten Mitra, Peter Müller, Subhajit Sengupta, Wentian Guo, Jonathan C. Silverstein, Ian Foster, Nigel Parsad, Kevin P. White, Yuan Ji*

*Corresponding author for this work

Research output: Contribution to journalArticle

16 Citations (Scopus)

Abstract

Background: Genetic interactions play a critical role in cancer development. Existing knowledge about cancer genetic interactions is incomplete, especially lacking evidences derived from large-scale cancer genomics data. The Cancer Genome Atlas (TCGA) produces multimodal measurements across genomics and features of thousands of tumors, which provide an unprecedented opportunity to investigate the interplays of genes in cancer. Methods: We introduce Zodiac, a computational tool and resource to integrate existing knowledge about cancer genetic interactions with new information contained in TCGA data. It is an evolution of existing knowledge by treating it as a prior graph, integrating it with a likelihood model derived by Bayesian graphical model based on TCGA data, and producing a posterior graph as updated and data-enhanced knowledge. In short, Zodiac realizes "Prior interaction map + TCGA data → Posterior interaction map." Results: Zodiac provides molecular interactions for about 200 million pairs of genes. All the results are generated from a big-data analysis and organized into a comprehensive database allowing customized search. In addition, Zodiac provides data processing and analysis tools that allow users to customize the prior networks and update the genetic pathways of their interest. Zodiac is publicly available at www.compgenome.org/ZODIAC. Conclusions: Zodiac recapitulates and extends existing knowledge of molecular interactions in cancer. It can be used to explore novel gene-gene interactions, transcriptional regulation, and other types of molecular interplays in cancer.

Original languageEnglish (US)
JournalJournal of the National Cancer Institute
Volume107
Issue number8
DOIs
StatePublished - Aug 1 2015

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ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Zhu, Yitan ; Xu, Yanxun ; Helseth, Donald L. ; Gulukota, Kamalakar ; Yang, Shengjie ; Pesce, Lorenzo Luigi ; Mitra, Riten ; Müller, Peter ; Sengupta, Subhajit ; Guo, Wentian ; Silverstein, Jonathan C. ; Foster, Ian ; Parsad, Nigel ; White, Kevin P. ; Ji, Yuan. / Zodiac : A Comprehensive Depiction of Genetic Interactions in Cancer by Integrating TCGA Data. In: Journal of the National Cancer Institute. 2015 ; Vol. 107, No. 8.
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abstract = "Background: Genetic interactions play a critical role in cancer development. Existing knowledge about cancer genetic interactions is incomplete, especially lacking evidences derived from large-scale cancer genomics data. The Cancer Genome Atlas (TCGA) produces multimodal measurements across genomics and features of thousands of tumors, which provide an unprecedented opportunity to investigate the interplays of genes in cancer. Methods: We introduce Zodiac, a computational tool and resource to integrate existing knowledge about cancer genetic interactions with new information contained in TCGA data. It is an evolution of existing knowledge by treating it as a prior graph, integrating it with a likelihood model derived by Bayesian graphical model based on TCGA data, and producing a posterior graph as updated and data-enhanced knowledge. In short, Zodiac realizes {"}Prior interaction map + TCGA data → Posterior interaction map.{"} Results: Zodiac provides molecular interactions for about 200 million pairs of genes. All the results are generated from a big-data analysis and organized into a comprehensive database allowing customized search. In addition, Zodiac provides data processing and analysis tools that allow users to customize the prior networks and update the genetic pathways of their interest. Zodiac is publicly available at www.compgenome.org/ZODIAC. Conclusions: Zodiac recapitulates and extends existing knowledge of molecular interactions in cancer. It can be used to explore novel gene-gene interactions, transcriptional regulation, and other types of molecular interplays in cancer.",
author = "Yitan Zhu and Yanxun Xu and Helseth, {Donald L.} and Kamalakar Gulukota and Shengjie Yang and Pesce, {Lorenzo Luigi} and Riten Mitra and Peter M{\"u}ller and Subhajit Sengupta and Wentian Guo and Silverstein, {Jonathan C.} and Ian Foster and Nigel Parsad and White, {Kevin P.} and Yuan Ji",
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Zhu, Y, Xu, Y, Helseth, DL, Gulukota, K, Yang, S, Pesce, LL, Mitra, R, Müller, P, Sengupta, S, Guo, W, Silverstein, JC, Foster, I, Parsad, N, White, KP & Ji, Y 2015, 'Zodiac: A Comprehensive Depiction of Genetic Interactions in Cancer by Integrating TCGA Data', Journal of the National Cancer Institute, vol. 107, no. 8. https://doi.org/10.1093/jnci/djv129

Zodiac : A Comprehensive Depiction of Genetic Interactions in Cancer by Integrating TCGA Data. / Zhu, Yitan; Xu, Yanxun; Helseth, Donald L.; Gulukota, Kamalakar; Yang, Shengjie; Pesce, Lorenzo Luigi; Mitra, Riten; Müller, Peter; Sengupta, Subhajit; Guo, Wentian; Silverstein, Jonathan C.; Foster, Ian; Parsad, Nigel; White, Kevin P.; Ji, Yuan.

In: Journal of the National Cancer Institute, Vol. 107, No. 8, 01.08.2015.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Zodiac

T2 - A Comprehensive Depiction of Genetic Interactions in Cancer by Integrating TCGA Data

AU - Zhu, Yitan

AU - Xu, Yanxun

AU - Helseth, Donald L.

AU - Gulukota, Kamalakar

AU - Yang, Shengjie

AU - Pesce, Lorenzo Luigi

AU - Mitra, Riten

AU - Müller, Peter

AU - Sengupta, Subhajit

AU - Guo, Wentian

AU - Silverstein, Jonathan C.

AU - Foster, Ian

AU - Parsad, Nigel

AU - White, Kevin P.

AU - Ji, Yuan

PY - 2015/8/1

Y1 - 2015/8/1

N2 - Background: Genetic interactions play a critical role in cancer development. Existing knowledge about cancer genetic interactions is incomplete, especially lacking evidences derived from large-scale cancer genomics data. The Cancer Genome Atlas (TCGA) produces multimodal measurements across genomics and features of thousands of tumors, which provide an unprecedented opportunity to investigate the interplays of genes in cancer. Methods: We introduce Zodiac, a computational tool and resource to integrate existing knowledge about cancer genetic interactions with new information contained in TCGA data. It is an evolution of existing knowledge by treating it as a prior graph, integrating it with a likelihood model derived by Bayesian graphical model based on TCGA data, and producing a posterior graph as updated and data-enhanced knowledge. In short, Zodiac realizes "Prior interaction map + TCGA data → Posterior interaction map." Results: Zodiac provides molecular interactions for about 200 million pairs of genes. All the results are generated from a big-data analysis and organized into a comprehensive database allowing customized search. In addition, Zodiac provides data processing and analysis tools that allow users to customize the prior networks and update the genetic pathways of their interest. Zodiac is publicly available at www.compgenome.org/ZODIAC. Conclusions: Zodiac recapitulates and extends existing knowledge of molecular interactions in cancer. It can be used to explore novel gene-gene interactions, transcriptional regulation, and other types of molecular interplays in cancer.

AB - Background: Genetic interactions play a critical role in cancer development. Existing knowledge about cancer genetic interactions is incomplete, especially lacking evidences derived from large-scale cancer genomics data. The Cancer Genome Atlas (TCGA) produces multimodal measurements across genomics and features of thousands of tumors, which provide an unprecedented opportunity to investigate the interplays of genes in cancer. Methods: We introduce Zodiac, a computational tool and resource to integrate existing knowledge about cancer genetic interactions with new information contained in TCGA data. It is an evolution of existing knowledge by treating it as a prior graph, integrating it with a likelihood model derived by Bayesian graphical model based on TCGA data, and producing a posterior graph as updated and data-enhanced knowledge. In short, Zodiac realizes "Prior interaction map + TCGA data → Posterior interaction map." Results: Zodiac provides molecular interactions for about 200 million pairs of genes. All the results are generated from a big-data analysis and organized into a comprehensive database allowing customized search. In addition, Zodiac provides data processing and analysis tools that allow users to customize the prior networks and update the genetic pathways of their interest. Zodiac is publicly available at www.compgenome.org/ZODIAC. Conclusions: Zodiac recapitulates and extends existing knowledge of molecular interactions in cancer. It can be used to explore novel gene-gene interactions, transcriptional regulation, and other types of molecular interplays in cancer.

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DO - 10.1093/jnci/djv129

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JO - Journal of the National Cancer Institute

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