v0.0.9

[0.0.9] - 2026-07-23

Added

• align_test_mask() aligns named treatment-by-gene diagnostic masks to
  existing causarray result tables without refitting effects or changing
  inference.
• summarize_treatment_associations() and
  plot_treatment_associations() diagnose treatment associations with both
  observed covariates and estimated latent factors.
• refit_propensity_scores() supports treatment-specific covariate removal and
  feature-specific logistic L2 penalties while preserving untreated score
  columns and reusable outcome predictions.
• The Replogle tutorial now compares Wilcoxon and causarray effect estimates in
  the extreme negative LFC tail, reports expression support, and demonstrates
  diagnostic support rules.

Changed

• Perturb-seq propensity diagnostics now include observed library size and a
  treatment-specific library-size regularization sensitivity analysis.
• Public diagnostics are documented in the README and LFC API guide, including
  the distinction between post-hoc result annotation and formal refitting or
  multiple-testing changes.
• summarize_treatment_associations() accepts bh_scope='per_treatment' to
  adjust within each treatment instead of across the whole treatment-by-covariate
  grid, and reports n_tests_in_family so the correction is self-describing.
• plot_treatment_associations() accepts an explicit symmetric vmax.
• plot_propensity_scores() accepts and forwards clip_bounds, which was
  previously fixed at its default in the summary it returns.
• refit_propensity_scores() reports degenerate_design and score_std per
  refitted treatment.

Fixed

• refit_propensity_scores() documented that carried-over score columns are
  preserved exactly, while clip was in fact applied to the whole returned
  matrix. The uniform behaviour is kept, since LFC consumes a single bound,
  but it is now stated and covered by a test. Pass clip=None to leave
  carried-over scores untouched.
• refit_propensity_scores() now warns when covariate filtering leaves a
  constant design, which previously collapsed to a covariate-free 0.5 score
  in silence and quietly turned AIPW into an unweighted contrast.
• A scalar clip raised TypeError: object of type 'float' has no len()
  instead of the documented ValueError in estimate_propensity_scores() and
  refit_propensity_scores().
• plot_treatment_associations() scaled the colour bar to the largest observed
  magnitude even for spearman_rho, which is bounded in [-1, 1]. Tiny
  correlations rendered as fully saturated and panels were not comparable
  across subsets; bounded statistics now use a fixed (-1, 1) range.
• summarize_propensity_scores() reported clipped_fraction = 0.0 for raw
  scores by inferring clipping from a default clip_bounds the caller may
  never have applied. clip_bounds=None now yields NaN.
• The Replogle propensity cache script derived log-library size from raw counts
  while prep_causarray_data derives it from capped counts, so its design
  matrix did not match the tutorial's. The script now caps first and asserts
  the preprocessing contract before fitting.