Package: mbkmeans 1.29.0

Davide Risso

mbkmeans: Mini-batch K-means Clustering for Single-Cell RNA-seq

Implements the mini-batch k-means algorithm for large datasets, including support for on-disk data representation.

Authors:Yuwei Ni [aut, cph], Davide Risso [aut, cre, cph], Stephanie Hicks [aut, cph], Elizabeth Purdom [aut, cph]

mbkmeans_1.29.0.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mbkmeans/json (API)

# Install 'mbkmeans' in R:

install.packages('mbkmeans', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/drisso/mbkmeans/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

On BioConductor:mbkmeans-1.29.0(bioc 3.24)mbkmeans-1.28.0(bioc 3.23)

clustering geneexpression rnaseq software transcriptomics sequencing singlecell human-cell-atlas openblas cpp

8.11 score 13 stars 2 packages 92 scripts 2 mentions 7 exports 74 dependencies

Last updated from:fbe387a8d0. Checks:1 WARNING, 8 NOTE, 1 OK, 4 FAIL. Indexed: yes.

Target	Result	Time	Files	Syslog
bioc-checks	WARNING	238
linux-devel-arm64	NOTE	380
linux-devel-x86_64	NOTE	467
source / vignettes	OK	404
linux-release-arm64	NOTE	378
linux-release-x86_64	NOTE	489
macos-release-arm64	NOTE	319
macos-release-x86_64	NOTE	473
macos-oldrel-arm64	FAIL	99
macos-oldrel-x86_64	FAIL	304
windows-devel	NOTE	616
windows-release	NOTE	741
windows-oldrel	FAIL	367
wasm-release	FAIL	753

Exports:blocksize compute_wcss mbkmeans MbkmeansParam mini_batch predict_mini_batch predict_mini_batch_r

Dependencies:abind askpass assorthead beachmat benchmarkme benchmarkmeData BH Biobase BiocGenerics biocmake BiocParallel cli ClusterR codetools cpp11 curl DelayedArray dir.expiry doParallel dplyr farver filelock foreach formatR futile.logger futile.options generics GenomicRanges ggplot2 glue gmp gtable httr IRanges isoband iterators jsonlite labeling lambda.r lattice lifecycle magrittr Matrix MatrixGenerics matrixStats mime openssl pillar pkgconfig R6 RColorBrewer Rcpp RcppArmadillo Rhdf5lib rlang S4Arrays S4Vectors S7 scales Seqinfo SingleCellExperiment snow SparseArray stringi stringr SummarizedExperiment sys tibble tidyselect utf8 vctrs viridisLite withr XVector

An introduction to mbkmeans

Installation | Introduction | Example dataset | mbkmeans | Choice of arguments | Batch size | Initialization | Running mbkmeans with multiple values of $k$ | Comparison with k-means | Use with bluster | Working with on-disk data in Bioconductor | References

Rendered fromVignette.Rmdusingknitr::rmarkdown

Last update: 2021-01-19
Started: 2018-11-06

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
blocksize	blocksize
Cluster rows of a matrix	clusterRows
Compute Whithin-Cluster Sum of Squares	compute_wcss
Mini-Batch k-means for large single cell sequencing data	mbkmeans mbkmeans,ANY-method mbkmeans,LinearEmbeddingMatrix-method mbkmeans,SingleCellExperiment-method mbkmeans,SummarizedExperiment-method
Mini-batch k-means clustering	MbkmeansParam show,MbkmeansParam-method
Mini_batch	mini_batch
Predict_mini_batch	predict_mini_batch
Compute labels for mini-batch k-means	predict_mini_batch_r

Usage by other packages (reverse dependencies)