Package: seurust 0.1.5

Nebil Ibrahim

seurust: 'Rust' Native Kernels for 'Seurat'

Provides 'Rust' implementations of performance-critical 'Seurat' native routines such as log-normalization, sparse row scaling, shared nearest-neighbor graph construction, and integration helpers. Install alongside 'Seurat' to use the same function signatures with a 'Rust' backend. Builds require 'Cargo' and 'rustc' (>= 1.81); CRAN source builds include offline crate sources under 'src/rust'.

Authors:Nebil Ibrahim [aut, cre], Rahul Satija [ctb], Satija Lab and Collaborators [cph]

seurust_0.1.5.tar.gz
seurust_0.1.5.zip(r-4.7-x86_64)seurust_0.1.5.zip(r-4.7-arm64)seurust_0.1.5.zip(r-4.6-x86_64)seurust_0.1.5.zip(r-4.6-arm64)seurust_0.1.5.zip(r-4.5-x86_64)
seurust_0.1.5.tgz(r-4.6-x86_64)seurust_0.1.5.tgz(r-4.6-arm64)seurust_0.1.5.tgz(r-4.5-x86_64)seurust_0.1.5.tgz(r-4.5-arm64)
seurust_0.1.5.tar.gz(r-4.7-arm64)seurust_0.1.5.tar.gz(r-4.7-x86_64)seurust_0.1.5.tar.gz(r-4.6-arm64)seurust_0.1.5.tar.gz(r-4.6-x86_64)
seurust_0.1.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
seurust/json (API)

# Install 'seurust' in R:
install.packages('seurust', repos = c('https://nebili.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nebili/seurust/issues

On CRAN:

Conda:

rustcargo

5.15 score 30 exports 2 dependencies

Last updated from:89f887c045 (on v0.1.5). Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK189
linux-devel-x86_64OK272
source / vignettesOK241
linux-release-arm64OK201
linux-release-x86_64OK229
macos-release-arm64OK157
macos-release-x86_64OK291
macos-oldrel-arm64OK160
macos-oldrel-x86_64OK306
windows-devel-arm64OK278
windows-devel-x86_64OK221
windows-release-arm64OK287
windows-release-x86_64OK200
windows-oldrel-x86_64OK187
wasm-releaseOK191

Exports:ComputeSNNDirectSNNToFilefast_distFastCovFastCovMatsFastExpMeanFastLogVMRFastRBindFastSparseRowScaleFastSparseRowScaleWithKnownStatsFindWeightsCGraphToNeighborHelperIntegrateDataCLogNormReplaceColsCrow_mean_dgcmatrixrow_sum_dgcmatrixrow_var_dgcmatrixRowMergeMatricesRowVarRunModularityClusteringCppRunUMISamplingRunUMISamplingPerCellScoreHelperSNN_SmallestNonzero_DistSparseRowVarSparseRowVar2SparseRowVarStdStandardizeWriteEdgeFile

Dependencies:latticeMatrix

Readme and manuals

Help Manual

Help pageTopics
Build a shared nearest-neighbor graphComputeSNN
Build an SNN graph and write it to a fileDirectSNNToFile
Distances between cells and their listed neighborsfast_dist
Fast covariance of a dense matrixFastCov
Fast cross-covariance of two dense matricesFastCovMats
Fast exp-mean of sparse matrix rowsFastExpMean
Fast log variance-to-mean ratioFastLogVMR
Fast row-bind of two dense matricesFastRBind
Scale and/or center sparse matrix rowsFastSparseRowScale
Scale sparse rows with known statisticsFastSparseRowScaleWithKnownStats
Find integration anchor weightsFindWeightsC
Convert a sparse graph to neighbor listsGraphToNeighborHelper
Integrate expression using anchor weightsIntegrateDataC
Log-normalize a sparse count matrixLogNorm
Replace columns of a sparse matrixReplaceColsC
Row means for dgCMatrix storagerow_mean_dgcmatrix
Row sums for dgCMatrix storagerow_sum_dgcmatrix
Row variances for dgCMatrix storagerow_var_dgcmatrix
Merge two sparse matrices by row namesRowMergeMatrices
Row variances of a dense matrixRowVar
Run modularity clustering on an SNN graphRunModularityClusteringCpp
Downsample UMIs globallyRunUMISampling
Downsample UMIs per cellRunUMISamplingPerCell
Score query cells using an SNN graphScoreHelper
Smallest non-zero SNN distancesSNN_SmallestNonzero_Dist
Sparse row variancesSparseRowVar
Sparse row variances given meansSparseRowVar2
Sparse row variances with clippingSparseRowVarStd
Standardize columns of a dense matrixStandardize
Write SNN edges to a fileWriteEdgeFile