Package: scmap 1.35.0

Vladimir Kiselev

scmap: A tool for unsupervised projection of single cell RNA-seq data

Single-cell RNA-seq (scRNA-seq) is widely used to investigate the composition of complex tissues since the technology allows researchers to define cell-types using unsupervised clustering of the transcriptome. However, due to differences in experimental methods and computational analyses, it is often challenging to directly compare the cells identified in two different experiments. scmap is a method for projecting cells from a scRNA-seq experiment on to the cell-types or individual cells identified in a different experiment.

Authors:Vladimir Kiselev

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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
scmap/json (API)

# Install 'scmap' in R:

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

Bug tracker:https://github.com/hemberg-lab/scmap/issues

Uses libs:

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

Datasets:

ann - Cell type annotations for data extracted from a publication by Yan et al.
yan - Single cell RNA-Seq data extracted from a publication by Yan et al.

On BioConductor:scmap-1.35.0(bioc 3.24)scmap-1.34.0(bioc 3.23)

immunooncology singlecell software classification supportvectormachine rnaseq visualization transcriptomics datarepresentation transcription sequencing preprocessing geneexpression dataimport bioconductor-package human-cell-atlas projection-mapping single-cell-rna-seq openblas cpp

9.10 score 100 stars 316 scripts 34 mentions 8 exports 55 dependencies

Last updated from:bc70ac79d2. Checks:1 WARNING, 11 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	WARNING	211
linux-devel-arm64	NOTE	249
linux-devel-x86_64	NOTE	345
source / vignettes	OK	288
linux-release-arm64	NOTE	254
linux-release-x86_64	NOTE	373
macos-release-arm64	NOTE	306
macos-release-x86_64	NOTE	328
macos-oldrel-arm64	NOTE	142
macos-oldrel-x86_64	NOTE	331
windows-devel	NOTE	251
windows-release	NOTE	201
windows-oldrel	NOTE	225
wasm-release	OK	164

Exports:getSankey indexCell indexCluster scmapCell scmapCell2Cluster scmapCluster selectFeatures setFeatures

Dependencies:abind Biobase BiocGenerics class cli cpp11 DelayedArray dplyr e1071 farver generics GenomicRanges ggplot2 glue googleVis gtable IRanges isoband jsonlite labeling lattice lifecycle magrittr MASS Matrix MatrixGenerics matrixStats pillar pkgconfig plyr proxy R6 randomForest RColorBrewer Rcpp RcppArmadillo reshape2 rlang S4Arrays S4Vectors S7 scales Seqinfo SingleCellExperiment SparseArray stringi stringr SummarizedExperiment tibble tidyselect utf8 vctrs viridisLite withr XVector

scmap package vignette

Rendered fromscmap.Rmdusingknitr::rmarkdown

Last update: 2023-05-15
Started: 2017-06-28

Help page	Topics
Cell type annotations for data extracted from a publication by Yan et al.	ann
The Euclidean Squared Norm of each column of a matrix is computed and the whole result is returned as a vector. Used as part of the approx. calculations of the cosine similarity between the query and the reference.	EuclSqNorm
Plot Sankey diagram comparing two clusterings	getSankey
Create an index for a dataset to enable fast approximate nearest neighbour search	indexCell indexCell,SingleCellExperiment-method indexCell.SingleCellExperiment
Create a precomputed Reference	indexCluster indexCluster,SingleCellExperiment-method indexCluster.SingleCellExperiment
Main nearest neighbour calculation function. Used on the first reference dataset. Returns a list of three objects: 1) the cell indices of the w nearest neighbours 2) the corresponding approx. cosine similarities	NN
Normalises each column of a matrix	normalise
For each cell in a query dataset, we search for the nearest neighbours by cosine distance within a collection of reference datasets.	scmapCell scmapCell,SingleCellExperiment-method scmapCell.SingleCellExperiment
Approximate k-NN cell-type classification using scfinemap	scmapCell2Cluster scmapCell2Cluster,list-method scmapCell2Cluster.SingleCellExperiment
scmap main function	scmapCluster scmapCluster,SingleCellExperiment-method scmapCluster.SingleCellExperiment
Find the most informative features (genes/transcripts) for projection	selectFeatures selectFeatures,SingleCellExperiment-method selectFeatures.SingleCellExperiment
Set the most important features (genes/transcripts) for projection	setFeatures setFeatures,SingleCellExperiment-method setFeatures.SingleCellExperiment
Computes the dot product between the subcentroids from the indexed reference and the subvectors of an element of the query dataset. Returns an M by k matrix. Used as an intermediate step (in NNfirst and NNmult) for calculating an approximation of the cosine similarity between the query and the reference.	subdistsmult
Single cell RNA-Seq data extracted from a publication by Yan et al.	yan

Package: scmap 1.35.0

scmap: A tool for unsupervised projection of single cell RNA-seq data

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