pysam
matplotlib
matplotlib_venn
scanpy[leiden,louvain]>=1.11
anndata>=0.8
numba>=0.57.0rc1
numpy>=2
kneed
qnorm
plotly
scipy>=1.14
statsmodels>=0.14.5
tqdm
pandas>1.5.3
seaborn>0.12
ipympl
ipywidgets>=8.0.0
scrublet
IPython
openpyxl
apybiomart
requests
python-gitlab
psutil
deprecation
pyyaml
beartype>=0.18.2
packaging
throttler
upsetplot
pptreport>=1.1.4
boto3
Jinja2

[all]
rpy2
anndata2ri
uropa
pybedtools>=0.9.1
pygenometracks>=3.8
peakqc
tobias>=0.17.2
click
bbknn
harmonypy
scanorama
scikit-learn
igraph
pycirclize>=1.7.1
liana
mudata>=0.3.1
networkx>=3.5
gseapy
pydeseq2>=0.5.2

[atac]
uropa
pybedtools>=0.9.1
pygenometracks>=3.8
peakqc
tobias>=0.17.2

[batch_correction]
bbknn
harmonypy
scanorama

[converter]
rpy2
anndata2ri

[core]
rpy2
anndata2ri
uropa
pybedtools>=0.9.1
pygenometracks>=3.8
peakqc
tobias>=0.17.2
click
bbknn
harmonypy
scanorama

[deseq2]
pydeseq2>=0.5.2

[downstream]
scikit-learn
igraph
pycirclize>=1.7.1
liana
mudata>=0.3.1
networkx>=3.5
gseapy
pydeseq2>=0.5.2

[gsea]
gseapy

[interactive]
click

[pseudotime]
scFates

[receptor_ligand]
scikit-learn
igraph
pycirclize>=1.7.1
liana
mudata>=0.3.1
networkx>=3.5
