Using supervised learning methods for gene selection in RNA-Seq case-control studies
This git repository contains the additional files used in the following research article: https://www.frontiersin.org/articles/10.3389/fgene.2018.00297/full
Running the code
The source code is currently split into different R source files, corresponding to the following steps:
- Data download from TCGA, save HTSeq-count files for all samples
- Run DESeq2 (normalization and differential expression analysis)
- Run random forests
- Survival analysis
The EPS method used to extract the other ranking of genes is run in parallel of step 3. The source code for the EPS method is available at: https://github.com/roohy/Extreme-Pseudo-Sampler/
Please note that
- Some variables may have to be modified in the R scripts (eg. baseDir) according to your system configuration.
- These R scripts rely heavily on external libraries which might be subject to change (especially TCGAbiolinks). If that were the case, some errors might occur.
Wenric S and Shemirani R (2018) Using Supervised Learning Methods for Gene Selection in RNA-Seq Case-Control Studies. Front. Genet. 9:297. doi: 10.3389/fgene.2018.00297