Genomic regression analysis of coordinated expression

被引：29

作者：

Cai, Ling ^{[1
,2
]}

Li, Qiwei ^{[2
]}

Du, Yi ^{[3
]}

Yun, Jonghyun ^{[4
]}

Xie, Yang ^{[2
]}

DeBerardinis, Ralph J. ^{[1
]}

Xiao, Guanghua ^{[2
]}

机构：

[1] UT Southwestern Med Ctr, Childrens Med Ctr, Res Inst, 6000 Harry Hines Blvd, Dallas, TX 75235 USA

[2] UT Southwestern Med Ctr, Quantitat Biomed Res Ctr, 5323 Harry Hines Blvd, Dallas, TX 75390 USA

[3] UT Southwestern Med Ctr, Dept Bioinformat, 5323 Harry Hines Blvd, Dallas, TX 75390 USA

[4] Univ Texas Arlington, Dept Math, 411S Nedderman Dr,478 Pickard Hall, Arlington, TX 76019 USA

来源：

NATURE COMMUNICATIONS | 2017年 / 8卷

关键词：

COPY NUMBER ALTERATION; HUMAN BREAST-TUMORS; GENE-EXPRESSION; CELL-LINE; TRANSCRIPTIONAL PROGRAM; CANCER; REVEALS; COEXPRESSION; SENSITIVITY; PROFILES;

D O I：

10.1038/s41467-017-02181-0

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Co-expression analysis is widely used to predict gene function and to identify functionally related gene sets. However, co-expression analysis using human cancer transcriptomic data is confounded by somatic copy number alterations (SCNA), which produce co-expression signatures based on physical proximity rather than biological function. To better understand gene-gene co-expression based on biological regulation but not SCNA, we describe a method termed "Genomic Regression Analysis of Coordinated Expression" (GRACE) to adjust for the effect of SCNA in co-expression analysis. The results from analyses of TCGA, CCLE, and NCI60 data sets show that GRACE can improve our understanding of how a transcriptional network is re-wired in cancer. A user-friendly web database populated with data sets from The Cancer Genome Atlas (TCGA) is provided to allow customized query.

引用

页数：10

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