decoupler 2.3.0 on Python PyPI

2.3.0

Updated the bundled decoupler Agent Skill, and decoupler-install-skills now supports multiple agent frameworks
pp.filter_by_prop now defaults to min_prop=0.1 (was 0.2) to match the value used in the vignettes
ds.msvisium now returns log-normalized data (sc.pp.normalize_total + sc.pp.log1p), with the log-normalized matrix also stored in adata.layers["norm"], instead of raw counts
Dropped support for Python 3.11; decoupler now requires Python 3.12 or newer
Updated to the scverse cookiecutter template v0.8.0 (hash-pinned GitHub Actions checked by zizmor, prek instead of pre-commit, sphinx-design instead of sphinx-tabs, shared Sphinx extensions from scverse-misc)

Fixed mt.ora selecting the bottom nvar - n_up features instead of the top n_up ones. Ranks are ascending, so the threshold is now nvar - n_up, restoring the behaviour of decoupler<2. With the default n_up (top 5%) this selected 95% of the features as observed, which also made mt.ora fail with invalid contingency table whenever nvar - n_up exceeded n_bg (#346)
Fixed n_bm in mt.ora selecting the bottom n_bm - 1 features instead of n_bm
mt.ora now validates that n_up and n_bm do not overlap and that n_bg is large enough for the number of selected features, instead of failing inside the Fisher exact test
mt.query_set now raises an informative error when n_bg is smaller than the number of features to test, instead of failing inside scipy.stats.fisher_exact
Fixed mt.gsea not shuffling the permutation indices when seed=0, which produced identical permutations and invalid p-values (#355)
Fixed mt.waggr folding its already two-sided permutation p-values as one-sided, which gave scores near 0 the smallest p-value (#373)
Fixed pl.dotplot showing an empty size legend when all dots have the same size (#370)
Fixed ds.msvisium failing with HTTP 403 by fetching the spot metadata from cells.ucsc.edu instead of the cells-test.gi.ucsc.edu mirror