Mutation
ActiveDriver
Reimand J, Bader GD. Systematic analysis of somatic mutations in phosphorylation signaling predicts novel cancer drivers. Mol Syst Biol. 2013;9:637.
Dendrix
Vandin F, Upfal E, Raphael BJ. De novo discovery of mutated driver pathways in cancer. Genome Res. 2012 Feb;22(2):375-85.
NetBox
Cerami E, Demir E, Schultz N, Taylor BS, Sander C. Automated network analysis identifies core pathways in glioblastoma. PLoS One. 2010 Feb 12;5(2):e8918.
MutSig2CV
Lawrence MS et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. 2013 Jul 11;499(7457):214-218.
MEMo
Ciriello G, Cerami E, Sander C, Schultz N. Mutual exclusivity analysis identifies oncogenic network modules. Genome Res. 2012 Feb;22(2):398-406.
DawnRank
Hou JP, Ma J. DawnRank: discovering personalized driver genes in cancer. Genome Med. 2014 Jul 31;6(7):56.
DriverNet
Bashashati A, Haffari G, Ding J, Ha G, Lui K, Rosner J, Huntsman DG, Caldas C, Aparicio SA, Shah SP. DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer. Genome Biol. 2012 Dec 22;13(12):R124.
e-Driver
Porta-Pardo E, Godzik A. e-Driver: a novel method to identify protein regions driving cancer. Bioinformatics. 2014 Nov 1;30(21):3109-14.
iPAC
Ryslik GA, Cheng Y, Cheung KH, Modis Y, Zhao H. Utilizing protein structure to identify non-random somatic mutations. BMC Bioinformatics. 2013 Jun 13;14:190.
MSEA
Jia P, Wang Q, Chen Q, Hutchinson KE, Pao W, Zhao Z. MSEA: detection and quantification of mutation hotspots through mutation set enrichment analysis. Genome Biol. 2014;15(10):489.
OncodriveCLUST
Tamborero D, Gonzalez-Perez A, Lopez-Bigas N. OncodriveCLUST: exploiting the positional clustering of somatic mutations to identify cancer genes. Bioinformatics. 2013 Sep 15;29(18):2238-44.
CoMET
Leiserson MD, Wu HT, Vandin F, Raphael BJ. CoMEt: a statistical approach to identify combinations of mutually exclusive alterations in cancer. Genome Biol. 2015 Aug 8;16:160.
MUTEX
Babur, Özgün, et al. Systematic identification of cancer driving signaling pathways based on mutual exclusivity of genomic alterations. Genome biology 16.1 (2015): 45.
DriverML
Han Y et al. DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies. Nucleic Acids Res. 2019 May 7;47(8):e45.
CNV
iGC
Lai, Y.P., Wang, L.B., Wang, W.A., Lai, L.C., Tsai, M.H., Lu, T.P. and Chuang, E.Y. (2017) iGC-an integrated analysis package of gene expression and copy number alteration. BMC Bioinformatics, 18, 35.
diggit
Alvarez, M.J., Chen, J.C. and Califano, A. (2015) DIGGIT: a Bioconductor package to infer genetic variants driving cellular phenotypes. Bioinformatics, 31, 4032-4034.
Methylation
Methylmix
Cedoz, P.L., Prunello, M., Brennan, K. and Gevaert, O. (2018) MethylMix 2.0: an R package for identifying DNA methylation genes. Bioinformatics, 34, 3044-3046.
ELMER
Silva, T.C., Coetzee, S.G., Gull, N., Yao, L., Hazelett, D.J., Noushmehr, H., Lin, D.C. and Berman, B.P. (2019) ELMER v.2: an R/Bioconductor package to reconstruct gene regulatory networks from DNA methylation and transcriptome profiles. Bioinformatics, 35, 1974-1977.