PyDESeq2
A Python implementation of the DESeq2 pipeline for bulk RNA-seq DEA. (by owkin)
zarp
The Zavolab Automated RNA-seq Pipeline (by zavolanlab)
| PyDESeq2 | zarp | |
|---|---|---|
| 2 | 1 | |
| 515 | 28 | |
| 3.5% | - | |
| 8.4 | 7.2 | |
| 8 days ago | about 2 months ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
PyDESeq2
Posts with mentions or reviews of PyDESeq2.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-07.
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DESeq2 Normalization
https://github.com/owkin/PyDESeq2/blob/main/pydeseq2/preprocessing.py I'm not sure but only a normalized count matrix seems not enough to do differential expression analysis. For example, in this script, it gathers also the size factor from the raw read count matrix. Maybe you could find it somewhere or recalculate it.
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When would you use R instead of Python?
PyDESeq2? https://github.com/owkin/PyDESeq2
zarp
Posts with mentions or reviews of zarp.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-05-11.
What are some alternatives?
When comparing PyDESeq2 and zarp you can also consider the following projects:
rnaseq - RNA-seq analyses.
atlas - ATLAS - Three commands to start analyzing your metagenome data
scanpy - Single-cell analysis in Python. Scales to >1M cells.
RNA-seq-analysis - RNAseq analysis notes from Ming Tang
diffexpr - Porting DESeq2 into python via rpy2
bioawk - BWK awk modified for biological data
py-shiny - Shiny for Python
sv-callers - Snakemake-based workflow for detecting structural variants in genomic data
metaGEM - :gem: An easy-to-use workflow for generating context specific genome-scale metabolic models and predicting metabolic interactions within microbial communities directly from metagenomic data