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Detecting hidden batch factors through data adaptive adjustment for biological effects

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DASC

Detecting hidden batch factors through data adaptive adjustment for biological effects

Overview

DASC is an R package used for identifying batches and classifying samples into different batches in a high dimensional gene expression dataset. The batch information can be further used as a covariate in conjunction with other variables of interest among standard bioinformatics analysis like differential expression analysis.

Installation

Dependencies

Before installing the package, please make sure the prerequisite packages described in DESCRIPTION file have been installed successfully. For example, cvxcluster needs to be installed from Eric Chi's github repository as it is not available through CRAN database.

To install the DASC package, start the terminal and enter:

On linux/MacOs

git clone https://github.com/HaidYi/DASC.git
R CMD build DASC
R CMD INSTALL DASC_*.tar.gz

Usage

For concrete usages, please refer the .html vignettes in inst/doc file.

References:

  1. Yi H*, Raman AT*, Zhang H, Allen GI, Liu Z. Detecting hidden batch factors through data-adaptive adjustment for biological effects. Bioinformatics (2018) (PMID: 29617963; PMCID: PMC6454417)
  2. Wang X, Yi H, Wang J, Liu Z, Yin Y, Zhang H. GDASC: a GPU parallel-based web server for detecting hidden batch factors. Bioinformatics (2020) (PMID: 32386292)

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