GeneExpressionSignature: an R package for discovering functional connections using gene expression signatures

被引:15
|
作者
Li, Fei [1 ]
Cao, Yang [1 ]
Han, Lu [1 ]
Cui, Xiuliang [1 ]
Xie, Dafei [1 ]
Wang, Shengqi [1 ]
Bo, Xiaochen [1 ]
机构
[1] Beijing Inst Radiat Med, Beijing 100850, Peoples R China
关键词
SET ENRICHMENT; PROFILES; DISEASE;
D O I
10.1089/omi.2012.0087
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Comparisons of gene expression signatures provide a way to explore functional connections among biological events in global aspects of cell response. GeneExpressionSignature is an R package developed for the large-scale analysis of gene expression signatures. The package implements two rank-merging algorithms and two similarity-scoring algorithms. The functions of GeneExpressionSignature provide a flexible solution for gene expression signature-based studies and hold great potential in biomedical research applications, such as drug repurposing. GeneExpressionSignature is released under GPL v2 within the Bioconductor project and is freely available at http://www.bioconductor.org/packages/release/bioc/html/GeneExpressionSignature.html.
引用
收藏
页码:116 / 118
页数:3
相关论文
共 50 条
  • [1] Genefu: an R/Bioconductor package for computation of gene expression-based signatures in breast cancer
    Gendoo, Deena M. A.
    Ratanasirigulchai, Natchar
    Schroeder, Markus S.
    Pare, Laia
    Parker, Joel S.
    Prat, Aleix
    Haibe-Kains, Benjamin
    [J]. BIOINFORMATICS, 2016, 32 (07) : 1097 - 1099
  • [2] Evaluating the Prognostic Gene Signatures in Bladder Cancer Using 'Curated Bladder Data' R Package
    Al-Dulaimi, Ragheed
    Muhammadi, Shakiba
    [J]. HUMAN HEREDITY, 2016, 81 (02) : 51 - 51
  • [3] GOexpress: an R/Bioconductor package for the identification and visualisation of robust gene ontology signatures through supervised learning of gene expression data
    Kévin Rue-Albrecht
    Paul A. McGettigan
    Belinda Hernández
    Nicolas C. Nalpas
    David A. Magee
    Andrew C. Parnell
    Stephen V. Gordon
    David E. MacHugh
    [J]. BMC Bioinformatics, 17
  • [4] NormExpression: An R Package to Normalize Gene Expression Data Using Evaluated Methods
    Wu, Zhenfeng
    Liu, Weixiang
    Jin, Xiufeng
    Ji, Haishuo
    Wang, Hua
    Glusman, Gustavo
    Robinson, Max
    Liu, Lin
    Ruan, Jishou
    Gao, Shan
    [J]. FRONTIERS IN GENETICS, 2019, 10
  • [5] GOexpress: an R/Bioconductor package for the identification and visualisation of robust gene ontology signatures through supervised learning of gene expression data
    Rue-Albrecht, Kevin
    McGettigan, Paul A.
    Hernandez, Belinda
    Nalpas, Nicolas C.
    Magee, David A.
    Parnell, Andrew C.
    Gordon, Stephen V.
    MacHugh, David E.
    [J]. BMC BIOINFORMATICS, 2016, 17
  • [6] xcore: an R package for inference of gene expression regulators
    Maciej Migdał
    Takahiro Arakawa
    Satoshi Takizawa
    Masaaki Furuno
    Harukazu Suzuki
    Erik Arner
    Cecilia Lanny Winata
    Bogumił Kaczkowski
    [J]. BMC Bioinformatics, 24
  • [7] xcore: an R package for inference of gene expression regulators
    Migdal, Maciej
    Arakawa, Takahiro
    Takizawa, Satoshi
    Furuno, Masaaki
    Suzuki, Harukazu
    Arner, Erik
    Winata, Cecilia Lanny
    Kaczkowski, Bogumil
    [J]. BMC BIOINFORMATICS, 2023, 24 (01)
  • [8] DysRegSig: an R package for identifying gene dysregulations and building mechanistic signatures in cancer
    Li, Quanxue
    Dai, Wentao
    Liu, Jixiang
    Sang, Qingqing
    Li, Yi-Xue
    Li, Yuan-Yuan
    [J]. BIOINFORMATICS, 2021, 37 (03) : 429 - 430
  • [9] SScore:: an R package for detecting differential gene expression without gene expression summaries
    Kennedy, RE
    Kerns, RT
    Kong, XR
    Archer, KJ
    Miles, MF
    [J]. BIOINFORMATICS, 2006, 22 (10) : 1272 - 1274
  • [10] DepthTools: an R package for a robust analysis of gene expression data
    Torrente, Aurora
    Lopez-Pintado, Sara
    Romo, Juan
    [J]. BMC BIOINFORMATICS, 2013, 14