chame
is work in progress. Active contributions via code or feedback are welcome.
chame
stands for a chromatin analysis module. It is being developed as a Python library for working with genomic ranges and chromatin accessibility in the scverse
ecosystem.
pip install git+https://github.com/gtca/chame
Raw data input: 10X Genomics ARC, ArchR (arrow files).
Data model: AnnData and MuData.
TF-IDF / LSI. TSS enrichment, mono-nucleosome occupancy, etc.
Differential accessibility, transcription factor activity, etc.
QC. Joint gene + peak visualisation.