Package: RCSL 1.13.0

Qinglin Mei

RCSL: Rank Constrained Similarity Learning for single cell RNA sequencing data

A novel clustering algorithm and toolkit RCSL (Rank Constrained Similarity Learning) to accurately identify various cell types using scRNA-seq data from a complex tissue. RCSL considers both lo-cal similarity and global similarity among the cells to discern the subtle differences among cells of the same type as well as larger differences among cells of different types. RCSL uses Spearman’s rank correlations of a cell’s expression vector with those of other cells to measure its global similar-ity, and adaptively learns neighbour representation of a cell as its local similarity. The overall similar-ity of a cell to other cells is a linear combination of its global similarity and local similarity.

Authors:Qinglin Mei [cre, aut], Guojun Li [fnd], Zhengchang Su [fnd]

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RCSL.pdf |RCSL.html✨
RCSL/json (API)

# Install 'RCSL' in R:

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

Bug tracker:https://github.com/qinglinmei/rcsl/issues

Datasets:

ann - Cell type annotations of 'yan' datasets by Yan et al.
yan - A public scRNA-seq dataset by Yan et al.

On BioConductor:RCSL-1.13.0(bioc 3.20)RCSL-1.12.0(bioc 3.19)

bioconductor-package

11 exports 0.71 score 70 dependencies 8 downloads

Last updated 2 months agofrom:124b95a039

Exports:BDSM EstClusters GenesFilter getLineage NeigRepresent PlotMST PlotPseudoTime PlotTrajectory RCSL SimS TrajectoryAnalysis

Dependencies:abind askpass Biobase BiocGenerics cli colorspace cpp11 crayon curl DelayedArray fansi farver GenomeInfoDb GenomeInfoDbData GenomicRanges ggplot2 glue gtable here httr igraph IRanges isoband jsonlite labeling lattice lifecycle magrittr MASS Matrix MatrixGenerics matrixStats mgcv mime munsell NbClust nlme openssl pillar pkgconfig png pracma R6 rappdirs RColorBrewer Rcpp RcppAnnoy RcppEigen RcppTOML reticulate rlang rprojroot RSpectra Rtsne S4Arrays S4Vectors scales SingleCellExperiment SparseArray SummarizedExperiment sys tibble UCSC.utils umap utf8 vctrs viridisLite withr XVector zlibbioc

A quick tour of RCSL

Qinglin Mei

Rendered fromRCSL.Rmdusingknitr::rmarkdownon Jun 30 2024.

Last update: 2024-02-15
Started: 2021-04-03

Help page	Topics
Cell type annotations of `yan` datasets by Yan et al.	ann
Calculate the bolock-diagnal matrix B min_B>=0, B1=1, F'F=I \|\|B - A\|\|_1 + r\|\|B\|\|^2 + 2lambdatrace(F'L*F)	BDSM
Solve the problem: min 1/2x'Lx-x'd s.t. x>=0, 1'x=1	EProjSimplexdiag
Estimate the optimal number of clusters C for clustering	EstClusters
Solve the problem: \|\|A-B\|\|^2 = \|\|A\|\|^2 + \|\|B\|\|^2 - 2A'B	EucDist
Perform the step of gene filtering to normalizaed gene expression data	GenesFilter
Infer the development lineage based on the clustering results from RCSL and the pseudotime	getLineage
Calculate the neighbor representation of cells to the low-dimensional gene expression matrix	NeigRepresent
Plot the visualization of constructed Minimum Spanning Tree based on the clustering results of RCSL	PlotMST
Infer the pseudo-temporal ordering between the cell types using the distance from a cell type to the predefined starting cell type.	PlotPseudoTime
Infer the developmental trajectories based on the clustering results from RCSL	PlotTrajectory
Perform the RCSL program	RCSL
Calculate the initial similarity matrix	SimS
Trajectory analysis	TrajectoryAnalysis
A public scRNA-seq dataset by Yan et al.	yan

Package: RCSL 1.13.0

RCSL: Rank Constrained Similarity Learning for single cell RNA sequencing data

A quick tour of RCSL

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