Package: scooter 0.0.0.9004

scooter: Streamlined scRNA-Seq Analysis Pipeline

Streamlined scRNA-Seq analysis pipeline.

Authors:Igor Dolgalev [cre, aut], Anna Yeaton [aut]

scooter_0.0.0.9004.tar.gz
scooter_0.0.0.9004.zip(r-4.7)scooter_0.0.0.9004.zip(r-4.6)scooter_0.0.0.9004.zip(r-4.5)
scooter_0.0.0.9004.tgz(r-4.6-any)scooter_0.0.0.9004.tgz(r-4.5-any)
scooter_0.0.0.9004.tar.gz(r-4.7-any)scooter_0.0.0.9004.tar.gz(r-4.6-any)
scooter_0.0.0.9004.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
scooter/json (API)

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

Bug tracker:https://github.com/igordot/scooter/issues

On CRAN:

Conda:

3.37 score 6 stars 79 scripts 43 exports 153 dependencies

Last updated from:2a639459d3. Checks:7 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR252
source / vignettesOK251
linux-release-x86_64ERROR251
macos-release-arm64ERROR176
macos-oldrel-arm64ERROR152
windows-develERROR213
windows-releaseERROR176
windows-oldrelERROR224
wasm-releaseOK178

Exports:.data%>%add_seurat_assayas_data_frame_seuratcalc_clust_averagescalculate_clusterscalculate_mito_pctcalculate_variancecheck_identity_columncreate_color_vectcreate_seurat_objdifferential_expression_per_clusterenexprenexprsenquoenquosensymensymsexprfilter_datageneset_scoreget_color_schemeget_dr_point_sizeget_test_counts_matriximport_mtxload_sample_counts_matrixlog_normalize_datamerge_metadatanormalize_dataplot_distributionquoquo_namequosrun_drrun_pcarun_tsnerun_umapsave_seurat_counts_matrixsctransform_dataset_identitysymsymswrite_message

Dependencies:abindaskpassbase64encBHbitbit64bitopsbslibcachemcaToolsclicliprclustercodetoolscommonmarkcowplotcpp11crayoncrosstalkcurldata.tabledeldirdigestdotCall64dplyrdqrngevaluatefarverfastDummiesfastmapfitdistrplusFNNfontawesomefsfuturefuture.applygenericsggplot2ggrepelggridgesggsciglobalsgluegoftestgplotsgridExtragtablegtoolsherehighrhmshtmltoolshtmlwidgetshttpuvhttricaigraphirlbaisobandjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevallifecyclelistenvlmtestmagrittrMASSMatrixmatrixStatsmemoisemimeminiUInlmeopensslotelparallellypatchworkpbapplypillarpkgconfigplotlyplyrpngpolyclipprettyunitsprogressprogressrpromisespurrrR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLreadrreshape2reticulaterlangrmarkdownROCRrprojrootRSpectraRtsneS7sassscalesscattermoresctransformSeuratSeuratObjectshinysitmosourcetoolsspspamspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrsurvivalsystensortibbletidyrtidyselecttinytextzdbutf8uwotvctrsviridisLitevroomwithrxfunxtableyamlzoo

Readme and manuals

Help Manual

Help pageTopics
Add assay to Seurat object.add_seurat_assay
Function to extract data from Seurat object.as_data_frame_seurat
Get cluster averages.calc_clust_averages
Run dimensionality reduction, pca, tse, and umapcalculate_clusters
Calculate mitochondrial percentage from Seurat object.calculate_mito_pct
Get variable genes and scale data.calculate_variance
Check identity of the Seurat object.check_identity_column
Function to create a color vector.create_color_vect
Create a new Seurat object from a matrix.create_seurat_obj
Calculate differential expression for one group versus alldifferential_expression_global
Calculate differential expression between specific groupsdifferential_expression_paired
Calculate differentially expressed genes within each subpopulation/clusterdifferential_expression_per_cluster
Filter cells based on the number of genes and mitochondrial reads.filter_data
Get geneset scores.geneset_score
Determine the color scheme.get_color_scheme
Determine the point size for reduced dimensions scatter plots (smaller for larger datasets).get_dr_point_size
Get an example counts matrix.get_test_counts_matrix
Read in 10x Genomics Cell Ranger Matrix Market format data.import_mtx
Read in Gene Expression and Antibody Capture data from a 10x Genomics Cell Ranger sparse matrix or from a text file.load_sample_counts_matrix
Log normalize data.log_normalize_data
Function to merge two metadata tables together.merge_metadata
Normalize datanormalize_data
Plot the distribution of specified features/variables.plot_distribution
Run dimensionality reduction, pca, tse, and umaprun_dr
Run PCArun_pca
Run TSNErun_tsne
Run UMAPrun_umap
Function to write Seurat counts matrix to csv.save_seurat_counts_matrix
SCT normalize data.sctransform_data
Set identity of the Seurat object.set_identity
Small function to write to message and to log file.write_message