PyDESeq2
rnaseq
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PyDESeq2
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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
rnaseq
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RNA seq bam files help?
A place to start https://github.com/davetang/rnaseq
What are some alternatives?
scanpy - Single-cell analysis in Python. Scales to >1M cells.
salmon - 🐟 🍣 🍱 Highly-accurate & wicked fast transcript-level quantification from RNA-seq reads using selective alignment
diffexpr - Porting DESeq2 into python via rpy2
rnaseqc - Fast, efficient RNA-Seq metrics for quality control and process optimization
zarp - The Zavolab Automated RNA-seq Pipeline
RNA-seq-analysis - RNAseq analysis notes from Ming Tang
py-shiny - Shiny for Python
bambu - Reference-guided transcript discovery and quantification for long read RNA-Seq data
mixcr - MiXCR is an ultimate software platform for analysis of Next-Generation Sequencing (NGS) data for immune profiling.
rnaseq - RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.
TPMCalculator - TPMCalculator quantifies mRNA abundance directly from the alignments by parsing BAM files