Package: SuperCell 1.0

The package maintainer

SuperCell: Simplification of scRNA-seq data by merging together similar cells

Aggregates large single-cell data into metacell dataset by merging together gene expression of very similar cells.

Authors:Mariia Bilous

SuperCell_1.0.tar.gz
SuperCell_1.0.zip(r-4.5)SuperCell_1.0.zip(r-4.4)SuperCell_1.0.zip(r-4.3)
SuperCell_1.0.tgz(r-4.4-any)SuperCell_1.0.tgz(r-4.3-any)
SuperCell_1.0.tar.gz(r-4.5-noble)SuperCell_1.0.tar.gz(r-4.4-noble)
SuperCell_1.0.tgz(r-4.4-emscripten)SuperCell_1.0.tgz(r-4.3-emscripten)
SuperCell.pdf |SuperCell.html
SuperCell/json (API)

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

Peer review:

Bug tracker:https://github.com/gfellerlab/supercell/issues

Datasets:

On CRAN:

softwarecoarse-grainingscrna-seq-analysisscrna-seq-data

8.12 score 67 stars 82 scripts 311 downloads 30 exports 154 dependencies

Last updated 4 months agofrom:5de820e93b. Checks:ERROR: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesFAILNov 05 2024
R-4.5-winNOTENov 05 2024
R-4.5-linuxNOTENov 05 2024
R-4.4-winNOTENov 05 2024
R-4.4-macNOTENov 05 2024
R-4.3-winNOTENov 05 2024
R-4.3-macNOTENov 05 2024

Exports:anndata_2_supercellbuild_knn_graphmetacell2_anndata_2_supercellsc_mixing_scoreSCimplifySCimplify_for_velocitySCimplify_from_embeddingsupercell_2_scesupercell_2_Seuratsupercell_assignsupercell_clustersupercell_DimPlotsupercell_estimate_velocitysupercell_FindAllMarkerssupercell_FindMarkerssupercell_GEsupercell_GeneGenePlotsupercell_mergesupercell_mergeGEsupercell_plotsupercell_plot_GEsupercell_plot_tSNEsupercell_plot_UMAPsupercell_prcompsupercell_puritysupercell_rescalesupercell_silhouettesupercell_tSNEsupercell_UMAPsupercell_VlnPlot

Dependencies:askpassassortheadbackportsbase64encBHBiocGenericsBiocNeighborsBiocParallelbitbit64blusterbootbroombslibcachemcheckmateclicliprclustercodetoolscolorspacecorpcorcowplotcpp11crayondata.tabledbscandigestdoFuturedplyrentropyevaluatefansifarverfastclusterfastmapfontawesomeforcatsforeachforeignformatRFormulafsfutile.loggerfutile.optionsfuturefuture.applygdatagenericsggplot2glmnetglobalsgluegridExtragtablegtoolshavenherehighrHmischmshtmlTablehtmltoolshtmlwidgetsigraphirlbaisobanditeratorsjomojquerylibjsonliteknitrlabelinglambda.rlatticelifecyclelistenvlme4magrittrMASSMatrixmatrixStatsmemoisemgcvmicemimeminqamitmlmunsellnlmenloptrnnetnumDerivopensslordinalpanparallellypatchworkpermutepillarpkgconfigplotfunctionsplyrpngprettyunitsprogressprogressrproxypurrrR6RANNrappdirsRColorBrewerRcppRcppEigenRcppTOMLreadrreticulaterlangrmarkdownrpartrprojrootRSpectrarstudioapiRtsneS4VectorssassscalesshapesnowstringistringrsurvivalsystibbletidyrtidyselecttinytexTraMineRtzdbucminfumaputf8vctrsveganvegclustviridisviridisLitevroomWeightedClusterweightswithrxfunyaml

Combined or independent SuperCell runs for different samples

Rendered fromb_Combined_vs_independent_sample_processing.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2022-07-18
Started: 2022-07-18

Example of the SuperCell pipeline

Rendered froma_SuperCell.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2023-09-13
Started: 2022-07-18

RNA-velocity for SuperCell

Rendered fromc_RNAvelocity_for_SuperCell.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2022-07-18
Started: 2022-07-18

Readme and manuals

Help Manual

Help pageTopics
Convert Anndata metacell object (Metacell-2 or SEACells) to Super-cell like objectanndata_2_supercell
Build kNN graphbuild_knn_graph
Build kNN graph using RANN::nn2 (used in '"build_knn_graph"')build_knn_graph_nn2
Cancer cell lines datasetcell_lines
Build kNN graph from distance (used in '"build_knn_graph"')knn_graph_from_dist
Convert Metacells (Metacell-2) to Super-cell like objectmetacell2_anndata_2_supercell
Pancreatic cell datasetpancreas
Compute mixing of single-cells within supercellsc_mixing_score
Detection of metacells with the SuperCell approachSCimplify
Construct super-cells from spliced and un-spliced matricesSCimplify_for_velocity
Detection of metacells with the SuperCell approach from low dim representationSCimplify_from_embedding
Super-cells to SingleCellExperiment objectsupercell_2_sce
Super-cells to Seurat objectsupercell_2_Seurat
Assign super-cells to the most aboundant clustersupercell_assign
Cluster super-cell datasupercell_cluster
Plot metacell 2D plot (PCA, UMAP, tSNE etc)supercell_DimPlot
Run RNAvelocity for super-cells (slightly modified from gene.relative.velocity.estimates) Not yet adjusted for super-cell size (not sample-weighted)supercell_estimate_velocity
Differential expression analysis of supep-cell data. Most of the parameters are the same as in Seurat FindAllMarkers (for simplicity)supercell_FindAllMarkers
Differential expression analysis of supep-cell data. Most of the parameters are the same as in Seurat FindMarkers (for simplicity)supercell_FindMarkers
Simplification of scRNA-seq datasetsupercell_GE
Simplification of scRNA-seq dataset (old version, not used since 12.02.2021)supercell_GE_idx
Gene-gene correlation plotsupercell_GeneGenePlot
Plot Gene-gene correlation plot for 1 featuresupercell_GeneGenePlot_single
Merging independent SuperCell objectssupercell_merge
Merging metacell gene expression matrices from several independent SuperCell objectssupercell_mergeGE
Plot metacell NWsupercell_plot
Plot super-cell NW colored by an expression of a gene (gradient color)supercell_plot_GE
Plot super-cell tSNE (Use supercell_DimPlot instead) Plots super-cell tSNE (result of supercell_tSNE)supercell_plot_tSNE
Plot super-cell UMAP (Use supercell_DimPlot instead) Plots super-cell UMAP (result of supercell_UMAP)supercell_plot_UMAP
compute PCA for super-cell data (sample-weighted data)supercell_prcomp
Compute purity of super-cellssupercell_purity
Rescale supercell objectsupercell_rescale
Compute Silhouette index accounting for samlpe size (super cells size) ###supercell_silhouette
Compute tSNE of super-cellssupercell_tSNE
Compute UMAP of super-cellssupercell_UMAP
Violin plotssupercell_VlnPlot
Plot Violin plot for 1 featuresupercell_VlnPlot_single