Fix plotting: per-module kME hub selection + working module-topology & preservation-lollipop plots - #5
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…r-module kME Both functions ranked every module's genes by a single fixed kME column (kme_cols[0]) instead of each module's own kME_<module>. As a result, for all modules except the one matching kme_cols[0], the kME barplot and the inner/outer rings of the module network plot showed the wrong module's hub genes. Now each module is ranked by its own kME_<module> column (falling back to the first kME column only if a per-module one is absent). hub_gene_network_plot and compute_module_umap were already correct and are unchanged. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…thon port
plot_module_preservation_lollipop previously expected the R-style
wd['module_preservation'][name] = {'Z': df} object with Zsummary.pres/moduleSize
columns, which this port never produces (module_preservation() returns a flat
DataFrame and does not store it), and it used an invalid matplotlib color
('grey75'). It now consumes the DataFrame returned by module_preservation()
directly (module / Zsummary / n_genes), shades the Z<2 (not preserved) and
2<=Z<10 (moderate) regions, sizes points by gene count, and colours by module.
module_topology_heatmap / module_topology_barplot relied on wd['degrees'], which
nothing in this port populates, so order_by/features='degree'/'weighted_degree'
failed. They now compute intramodular connectivity (degree, weighted_degree)
from the TOM on the fly. The heatmap also blanks the lower triangle via NaN
(with cmap.set_bad) instead of clipping it into the color range.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…ectly
The kME columns were detected with `"kME" in c.lower()`, but lowercasing the
column name means the mixed-case literal "kME" can never match — so the list was
always empty. In module_network_plot this skipped the top-N hub selection
entirely and plotted every gene in the module (hundreds) instead of
n_inner+n_outer. Fixed to a case-consistent check ("kme" in c.lower()) in all
seven occurrences.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
scipy 1.18 changed rankdata(method="ordinal") to return float64 ranks, which NumPy 2 rejects as array indices, crashing cutreeHybrid deep inside dynamicTreeCut (clusts[rnk[0] - 1]) and breaking the Python 3.12 CI job. Inject an integer-coercing rankdata into dynamicTreeCut's module globals (alongside the existing df_apply shim) so ordinal ranks stay integer-typed. The cast is lossless (ordinal ranks are whole numbers) and a no-op on older scipy, so the passing 3.9-3.11 jobs are unaffected. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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