Package: scAnnotatR 1.13.0

Johannes Griss

scAnnotatR: Pretrained learning models for cell type prediction on single cell RNA-sequencing data

The package comprises a set of pretrained machine learning models to predict basic immune cell types. This enables all users to quickly get a first annotation of the cell types present in their dataset without requiring prior knowledge. scAnnotatR also allows users to train their own models to predict new cell types based on specific research needs.

Authors:Vy Nguyen [aut], Johannes Griss [cre]

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scAnnotatR.pdf |scAnnotatR.html
scAnnotatR/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/grisslab/scannotatr/issues

Datasets:

On BioConductor:scAnnotatR-1.13.0(bioc 3.21)scAnnotatR-1.12.0(bioc 3.20)

singlecelltranscriptomicsgeneexpressionsupportvectormachineclassificationsoftware

6.64 score 15 stars 16 scripts 486 downloads 17 exports 205 dependencies

Last updated 23 days agofrom:108d23b755. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-winWARNINGOct 31 2024
R-4.5-linuxWARNINGOct 31 2024
R-4.4-winWARNINGOct 31 2024
R-4.4-macWARNINGOct 31 2024
R-4.3-winWARNINGOct 31 2024
R-4.3-macWARNINGOct 31 2024

Exports:caret_modelcell_typecell_type<-classify_cellsdelete_modelload_modelsmarker_genesp_thresp_thres<-parentplant_treeplot_roc_curvesave_new_modelscAnnotatRshowtest_classifiertrain_classifier

Dependencies:abindAnnotationDbiAnnotationHubapeaskpassbase64encBHBiobaseBiocFileCacheBiocGenericsBiocManagerBiocVersionBiostringsbitbit64bitopsblobbslibcachemcaretcaToolsclasscliclockclustercodetoolscolorspacecommonmarkcowplotcpp11crayoncrosstalkcurldata.tabledata.treeDBIdbplyrDelayedArraydeldirdiagramdigestdotCall64dplyrdqrnge1071evaluatefansifarverfastDummiesfastmapfilelockfitdistrplusFNNfontawesomeforeachfsfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelggridgesglobalsgluegoftestgowergplotsgridExtragtablegtoolshardhatherehighrhtmltoolshtmlwidgetshttpuvhttricaigraphipredIRangesirlbaisobanditeratorsjquerylibjsonliteKEGGRESTkernlabKernSmoothknitrlabelinglaterlatticelavalazyevalleidenlifecyclelistenvlmtestlubridatemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimeminiUIModelMetricsmunsellnlmennetnumDerivopensslparallellypatchworkpbapplypillarpkgconfigplogrplotlyplyrpngpolyclippROCprodlimprogressrpromisesproxypurrrR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLrecipesreshape2reticulaterlangrmarkdownROCRrpartrprojrootRSpectraRSQLiteRtsneS4ArraysS4VectorssassscalesscattermoresctransformSeuratSeuratObjectshapeshinySingleCellExperimentsitmosourcetoolsspspamSparseArrayspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsSQUAREMstringistringrSummarizedExperimentsurvivalsystensortibbletidyrtidyselecttimechangetimeDatetinytextzdbUCSC.utilsutf8uwotvctrsviridisLitewithrxfunxtableXVectoryamlzlibbioczoo

Introduction to scAnnotatR

Rendered fromclassifying-cells.Rmdusingknitr::rmarkdownon Oct 31 2024.

Last update: 2021-07-30
Started: 2020-11-10

Training basic model classifying a cell type from scRNA-seq data

Rendered fromtraining-basic-model.Rmdusingknitr::rmarkdownon Oct 31 2024.

Last update: 2024-03-21
Started: 2020-11-10

Training model classifying a cell subtype from scRNA-seq data

Rendered fromtraining-child-model.Rmdusingknitr::rmarkdownon Oct 31 2024.

Last update: 2024-03-21
Started: 2020-11-10

Readme and manuals

Help Manual

Help pageTopics
caret_modelcaret_model
cell_typecell_type cell_type<-,scAnnotatR-method
Setter for cell_type. Change cell type of a classifiercell_type<-
Internal functions of scAnnotatR packagebalance_dataset caret_model<- caret_model<-,scAnnotatR-method checkCaretModelValidity checkCellTypeValidity checkMarkerGenesValidity checkObjectValidity checkParentValidity checkPThresValidity check_parent_child_coherence classify_cells_sce classify_cells_seurat classify_clust construct_tag_vect download_data_file filter_cells make_prediction marker_genes<- marker_genes<-,scAnnotatR-method parent<- parent<-,scAnnotatR-method preprocess_sce_object preprocess_seurat_object process_parent_classifier select_marker_genes simplify_prediction subset_models test_classifier_from_mat test_classifier_sce test_classifier_seurat test_performance train_classifier_from_mat train_classifier_sce train_classifier_seurat train_func transform_to_zscore verify_parent
Classify cells from multiple modelsclassify_cells
Delete model/branch from packagedelete_model
Load classifiers from databasesload_models
marker_genesmarker_genes
p_thresp_thres p_thres<-,scAnnotatR-method
Setter for predicting probability thresholdp_thres<-
parentparent
Plant tree from list of modelsplant_tree
Plot roc curveplot_roc_curve
Save a model to the packagesave_new_model
scAnnotatR class.scAnnotatR
Show objectshow,scAnnotatR-method
Testing process.test_classifier test_classifier,scAnnotatR-method
A Seurat Object Sampletirosh_mel80_example
Train cell type classifiertrain_classifier