Based on the implementation in EdgeR Bioconductor package.
tmma can be installed through pip:
pip install git+https://github.com/lukauskas/tmma.git
For development, please clone the repository:
git clone https://github.com/lukauskas/tmma.git
and then install package with (-e) flag set and optional test dependencies.
pip install -e .[test]
If you have installed the development version of the package, you can run the tests with the following command:
python -m unittest discover -s tests/
See example based on the Arabidopsis dataset from edgeR user guide, available
in the examples directory
- Robinson, M., McCarthy, D., Smyth, G. (2009). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data Bioinformatics 26(1), 139-140. https://dx.doi.org/10.1093/bioinformatics/btp616
- Robinson, M., Oshlack, A. (2010). A scaling normalization method for differential expression analysis of RNA-seq data Genome Biology 11(3), R25. https://dx.doi.org/10.1186/gb-2010-11-3-r25
- McCarthy, D., Chen, Y., Smyth, G. (2012). Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation Nucleic Acids Research 40(10), 4288-4297. https://dx.doi.org/10.1093/nar/gks042