Sped up MNN pair finding: FindMnnPairs() scanned the
full neighbor tables with which() for every cell and grew
its result with repeated rbind() calls inside a loop, both
of which scaled quadratically in cell count. Both are now near-linear,
with no change in output (verified byte-identical against the previous
implementation). Fuzzy() also no longer converts its
correction matrix to a data.frame just to track a per-cell
flag, which was much slower than tracking it as a plain vector. Together
these give roughly a 2-4x speedup on real datasets, more on larger ones,
since MNN search is repeated on every maxLoop
pass.
Added an ncores parameter
(CorrectBatches(), CorrectBatch(),
GetMnnPairs(), and via ... on
RunCanek()) to parallelize the two independent
k-nearest-neighbor searches MNN pair finding requires. Defaults to 1
(fully sequential) — parallelism is opt-in only, since automatically
detecting and using “available” cores could oversubscribe a shared
cluster/HPC job’s actual allocation. Uses
parallel::mclapply(), so ncores > 1
requires Linux/macOS (errors on Windows, and if more cores are requested
than parallel::detectCores() reports, rather than silently
falling back or capping). See the new Speed
up batch correction with parallel processing vignette.
RunCanek() on Seurat objects now defaults to
correctEmbeddings = TRUE: correction happens in
PCA-embedding space instead of on gene expression directly, and the
result is stored as a new "canek" dimensionality reduction
rather than a new "Canek" assay. Code that reads
assay = "Canek" after RunCanek() needs
updating — use Embeddings(x, "canek") instead, or pass
correctEmbeddings = FALSE to keep the original assay-based
behavior.pcaDim is now inferred automatically from an
existing "pca" reduction on the object when not specified,
instead of always defaulting to 50; falls back to 30 with a warning if
no "pca" reduction exists.
When correctEmbeddings = TRUE and a
"pca" reduction already exists, RunCanek()
reuses it directly instead of recomputing one internally (new
precomputedEmbeddings parameter on
CorrectBatches()/ CorrectBatch()).
Added SCTransform support: RunCanek() auto-detects
an existing "SCT" assay, and for
correctEmbeddings = TRUE requires an existing
"pca" reduction computed on properly reconciled data (see
SCTransform documentation). Errors with guidance towards the
reconciliation steps (SelectIntegrationFeatures() +
PrepSCTIntegration()) are thrown.
Added a iterative-correction loop for
correctEmbeddings = TRUE: new
maxLoop/loopTol parameters
(RunCanek() on Seurat objects defaults to
maxLoop = 5) iterate the correction, feeding each pass’s
result into the next, and stop early once further passes stop improving
the correction.
Fixed a bug where clustering and the fuzzy logic step would error
(subscript out of bounds) whenever
correctEmbeddings = TRUE was used with pcaDim
below 10.
Rewrote the Seurat vignette and added a new SCTransform vignette demonstrating the current default workflow for each normalization method. Pre-0.3.0 vignettes are archived under Previous versions.
Fix bug when using SCTransform. (#14)
Add BugReports and URL.(#13)
Relaxing tests to no consider the names attribute.(#12)
Refactor RunCanek() Seurat and SingleCellExperiment
interfaces to preserve original objects.
Added integration.name argument to RunCanek() to
customize the name of the integrated assay.
test-Clustering unit-test for latest
igraph version. (#7)
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