It seems that most differential gene expression packages for RNA-Seq are written in R.
Examples include:
- edgeR
- limma
- DESeq
Are any similar (and easy to use) packages available for Python, or have any of the R packages been ported?
The best I could find was:
- https://bcbio.wordpress.com/2009/09/13/differential-expression-analysis-with-bioconductor-and-python/
- http://dept.stat.lsa.umich.edu/~kshedden/Python-Workshop/gene_expression_comparison.html
But I really don't want to use rpy2 (_1st link_). The second link is probably where I would start, but I first wanted to make sure I'm not reinventing the wheel.
SIDE NOTE:
This question was asked on Stackoverflow (https://stackoverflow.com/questions/36305682/differential-gene-expression-analysis-in-python), but closed because your not allowed to ask for suggestions on tools (please explain all the upvotes then), but in any case, I thought I'd bring it over to this forum for suggestions.
The only comment I would like to express is that you should take into account that the mentioned tools working under R are very well known, have been used in a miriad of experiments, have their sources publicly available so they have been analyzed by many potential users, and because of that, they are the recommended for most of the cases.
scanpy
usesdiffxpy
to run DE analysis, BUT, keep in mind thatscanpy
is for single-cell RNA-Seq, not bulk.