add MiloDE (#1001)

* milo: add de_nhoods (miloDE) for per-neighbourhood DE testing

For each nhood, pseudobulks cells by sample (sc.get.aggregate), fits the
existing PyDESeq2 or Statsmodels DE model, and applies the two-axis
correction miloDE uses: BH across genes within each nhood and
density-weighted BH across nhoods per gene. The weighted-BH used by
da_nhoods is factored out into a shared _weighted_bh helper.

Validated against miloDE R on synthetic data: median Spearman(logFC) =
0.996 across genes per nhood, 100% sign-concordance on R-significant
entries.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: add docstring preview for milo.de_nhoods

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* milo: de_nhoods returns long DataFrame, matching pertpy DE convention

Switch return type from AnnData(n_nhoods × n_genes) to a long DataFrame
with columns (nhood, variable, log_fc, p_value, adj_p_value,
pval_corrected_across_nhoods, test_performed) — same shape pertpy's
other DE methods produce and the same shape miloDE R returns.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: add example previews for milo.de_nhoods plotting recipes

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* milo: add plot_de_nhood_graph for one-line per-gene DE visualization

Pairs with de_nhoods the same way plot_nhood_graph pairs with da_nhoods:
takes the long DataFrame + a gene name and renders the nhood graph
colored by that gene's logFC, masking nhoods above the spatial-FDR
threshold. The rendering body shared with plot_nhood_graph is factored
into a private _render_nhood_graph helper to avoid duplication.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: bump tutorials submodule for miloDE section

Pulls in scverse/pertpy-tutorials#61 which appends a Milo.de_nhoods +
plot_de_nhood_graph demonstration to milo.ipynb.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* milo: silence per-nhood pydeseq2 stdout in de_nhoods + bump tutorial

PyDESeq2 prints progress per fit; calling it once per nhood otherwise
floods stdout. Wrap the per-nhood model fit/test in
contextlib.redirect_stdout so de_nhoods runs cleanly.

Re-points the tutorials submodule to scverse/pertpy-tutorials@cffc9b5
which adds the miloDE section to milo.ipynb, with warnings filtered at
the top of the notebook so per-nhood validity messages and small-sample
PyDESeq2 warnings don't drown out cell outputs.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: bump tutorials submodule to kang_2018-based miloDE example

scverse/pertpy-tutorials@9ff43c2 switches the miloDE tutorial section
to kang_2018 (8 patients × ctrl/stim, raw counts in .X) so the example
recovers ISG15 / ISG20 as top hits rather than mostly-NaN results.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* milo: float64 p-values in de_nhoods + summarize skipped nhoods once

Two related fixes plus a tutorials submodule bump.

de_nhoods previously stored p-values as float32, which underflows to
zero below ~1.4e-45. Strong DE signals (IFN-β ISGs in the kang_2018
example) routinely produce p ~ 1e-200 from PyDESeq2, which was getting
silently clamped to 0 in both the raw p_value and adj_p_value columns
(and hence pval_corrected_across_nhoods too). Storing p-values in
float64 fixes it; logFC stays float32.

Also collapses the per-nhood `Nhood X: DE test failed (...)` logger
warnings (one per skipped nhood) into a single end-of-run summary, so
the tutorial doesn't have to reach into pertpy._logger to silence
them.

Tutorials submodule bumps to scverse/pertpy-tutorials@a0b9e84, which
drops the pertpy._logger import from milo.ipynb and re-executes against
this fix (top hits now show p_value ~ 1e-73, not 0).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: point tutorials submodule at pertpy-tutorials main

The miloDE tutorial section landed via scverse/pertpy-tutorials#61
(squashed to d2ab4bf on main); move the pinned commit from the
feature-branch tip to the merged main commit.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs: regenerate de_nhoods preview with kang_2018 / ISG15

Matches the tutorial example. The synthetic-data version was less
informative.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

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Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: Zethson