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presto 1.1.0

First CRAN release. Version 1.0.0 refers to the pre-CRAN package installed from GitHub.

New features

• wilcoxauc() accepts disk-backed DelayedMatrix input (e.g. HDF5-backed assays from HDF5Array), processed in feature blocks so the whole matrix never has to be loaded in memory (#26). Other matrix-like classes with an as(., "dgCMatrix") method (e.g. BPCells) are coerced automatically.
• wilcoxauc() gains a transposed argument for observations x features input (samples in rows), which runs directly on that layout without materializing a transposed copy (#18).
• wilcoxauc() gains an nthreads argument: the per-feature ranking of sparse (dgCMatrix) input can run multithreaded. Results are identical at any thread count; roughly 2.6x faster with 4 threads on a 3,000 x 80,000 matrix. The default (nthreads = 1) is unchanged.
• New toy_seurat() and toy_sce() generate small example Seurat / SingleCellExperiment objects on the fly with the installed package versions, so they can never go stale.
• Two vignettes: Getting started with presto and Pseudobulk differential expression with DESeq2, both worked through on a real 25,341-cell colon CD8 T-cell dataset (GSE206299, Thomas et al. 2024).

Breaking changes

• wilcoxauc() now stops with an informative error when X contains NA values, instead of silently returning incorrect results (#25).
• The shipped object_seurat and object_sce datasets were removed; use toy_seurat() and toy_sce() instead.
• Rcpp and data.table moved from Depends to Imports, so they are no longer attached to the search path when presto is loaded.

Bug fixes

• The Wilcoxon variance correction now includes every tie group: the final tie group per feature and the implicit-zero group of all-zero features used to be dropped, inflating p-values on heavily tied data (#29). P-values now agree with stats::wilcox.test() to machine precision; on typical count data the change is tiny (< 1e-4), but it is meaningful for binary or heavily tied features. Constant features report pval = 1 instead of an arbitrary value.
• wilcoxauc() and rank_matrix() no longer modify their input in place: dense input used to be silently overwritten with ranks via an aliased memory buffer (#7). Dense avgExpr and logFC are computed from the original values (also #7).
• The Seurat dispatcher of wilcoxauc() uses the layer argument required by Seurat 5 (#44).
• pseudobulk_within() handles character and multi-level contrast variables.
• pseudobulk_pairwise() no longer fails on single-column meta_data.
• collapse_counts() no longer drops a single-column meta_data to a vector, which had broken the collapse_background = TRUE path of pseudobulk_deseq2().
• sumGroups() and nnzeroGroups() accept a character group vector y again. A character y previously coerced to NA via as.integer(), producing an out-of-bounds index that crashed on some platforms; the labels are now factored first, and NA labels raise a clear error.
• summarize_dge_pairs() no longer prints debug output, and pseudobulk_deseq2() no longer warns unconditionally.
• Replaced deprecated .data$ tidyselect usage and superseded tidyr::spread() with tidyr::pivot_wider() in top_markers() and top_markers_dds() (#20).

Performance

• The sparse-input statistics of wilcoxauc() (transpose, ranking, and all group-wise reductions) are fused into a single-pass C++ kernel, about 12% faster serially before any threading.

presto 1.0.0

• Original GitHub release.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.