Wilcoxon rank-sum addition to rank_genes_groups #487
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Hi,
This work introduces a CuPy-based GPU implementation of the Wilcoxon rank-sum test for rank_genes_groups().
Key changes
GPU acceleration: Rank computation, group rank sums, z-scores, and two-sided p-values are computed on the GPU (CuPy + cupyx.scipy.special.ndtr).
Vectorized group operations: Replace per-group loops with a single matrix multiply
group_matrix.T @ ranksto obtain all group rank sums at once.GPU-native rank computation: Mid-ranks and tie-correction implemented via CuPy primitives (cp.argsort, cp.cumsum) to mirror Scanpy semantics.
Dynamic GPU memory management:
_choose_chunk_size()queriescp.cuda.runtime.memGetInfo()to size gene chunks adaptively (avoids OOM and maximizes throughput).Testing:
Added
tests/test_rank_genes_groups_wilcoxon.pyto ensure same output as Scanpy’s wilcoxon rank_genes_groups.