This repository supplies the code developed in the study of Torang et al. "An elastic-net logistic regression approach to generate classifiers and gene signatures for types of immune cells and T helper cell subsets". The corresponding pre-print can be found on bioRxiv ( https://doi.org/10.1101/623082 ). It can be used to reproduce the results of the study and investigate the methodology to be used for other datasets.
- R version 3.5.3 -- "Joy in Playing").
- R libraries: dplyr, annotables, EDASeq, glmnet, DescTools, matlab, tidyverse, plotrix, MASS, plyr, rafalib, factoextra, NbClust, Matrix, pROC, xlsx, MESS, ggplot2
All necessary data is provided in the "Files" folder of the repository or can be found in Gene Expression Omnibus repository [https://www.ncbi.nlm.nih.gov] with the following GEO accession numbers: GSE60424, GSE64655, GSE36952, GSE84697, GSE74246, GSE70106, GSE55536, GSE71645, GSE66261, GSE96538, GSE75688, GSE72056. Sourcing for all data can be found in Torang et al.
To reproduce the results, download the relevant script and load the corresponding data into the R workspace. Running the script will generate all relevant figures and data tables for the given portion of the study.
The code provided in this repository reproduces the main results of the study of Torang et al. "An elastic-net logistic regression approach to generate classifiers and gene signatures for types of immune cells and T helper cell subsets" but it is not meant as a self-contained module for use in further analysis.
Torang et al. An elastic-net logistic regression approach to generate classifiers and gene signatures for types of immune cells and T helper cell subsets. Pre-print on bioRxiv https://doi.org/10.1101/623082