bacr
bacr is an R package that implements the Bayesian Adjustment for Confounding (BAC) method for estimating the average causal effect of a treatment on an outcome from cohort studies. The software package is available at CRAN.
References
- Wang C, Parmigiani G, Dominici F and Zigler CM. Accounting for Uncertainty in Confounder and Effect Modifier Selection when Estimating Average Causal Effects in Generalized Linear Models. Biometrics, 71(3):654-65, 2015.
- Wang C, Parmigiani G and Dominici F. Bayesian Effect Estimation Accounting for Adjustment Uncertainty (with discussion). Biometrics, 68(3):661-71, 2012.
NanoStringDiff
NanoStringDiff is an R package to perform differential expression analysis based on gene expression data generated from the NanoString nCounter system. The software package is available at Bioconductor.
Reference
- Wang H, Horbinski C, Wu H, Liu Y, Sheng S, Liu J, Weiss H, Stromberg A, Wang C. NanoStringDiff: A Novel Statistical Method for Differential Expression Analysis Based on NanoString nCounter Data. Nucleic Acids Research, 44(20): e151, 2016.
SDAMS
SDAMS is an R package that implements a semiparametric method for differential abundance analysis of proteomic and metabolomic data. The software package is available at Bioconductor.
Reference
- Li Y, Fan TWM, Lane AN, Kang WK, Arnold SM, Stromberg AJ, Wang C*, Chen Li*. SDA: A semi-parametric differential abundance analysis method for metabolomics and proteomics data. BMC Bioinformatics, 20(1):501, 2019. * Co-corresponding authors
PATOPA
PATOPA is a bioinformatics software to delineate the temporal order of driver mutations during carcinogenesis by leveraging functional annotation and pathway information. The software is available at GitHub.
Reference
- Wang M, Yu T, Liu J, Chen L, Stromberg AJ, Villano JL, Arnold SM, Liu C, Wang C. A probabilistic method for leveraging functional annotations to enhance estimation of the temporal order of pathway mutations during carcinogenesis. BMC bioinformatics, 20:620, 2019.
DASEV
DASEV is an R package that implements a two-part model with Bayesian shrinkage estimation of variance for differential abundance analysis of proteomic and metabolomic data. The software package is available here.
Reference
- Huang Z, Lane AN, Fan TW, Higashi RM, Weiss HL, Yin X, Wang C. Differential Abundance Analysis with Bayes Shrinkage Estimation of Variance (DASEV) for Zero-Inflated Proteomic and Metabolomic Data. Scientific Reports, 10(1):876, 2020.
MEScan
MEScan is a bioinformatics software to identify cancer driver mutations by genome-wide screen of mutually exclusive mutation patterns. The software is available at GitHub.
Reference
- Liu S, Liu J, Xie Y, Zhai T, Hinderer EW, Stromberg AJ, Canderford NL, Kolesar JM, Moseley HNB, Chen L, Liu C, Wang C. MEScan: a powerful statistical framework for genome-scale mutual exclusivity analysis of cancer mutations. Bioinformatics, btaa957, 2020.