Package: scAnnotatR 1.11.0
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:
scAnnotatR_1.11.0.tar.gz
scAnnotatR_1.11.0.zip(r-4.5)scAnnotatR_1.11.0.zip(r-4.4)scAnnotatR_1.11.0.zip(r-4.3)
scAnnotatR_1.11.0.tgz(r-4.4-any)scAnnotatR_1.11.0.tgz(r-4.3-any)
scAnnotatR_1.11.0.tar.gz(r-4.5-noble)scAnnotatR_1.11.0.tar.gz(r-4.4-noble)
scAnnotatR_1.11.0.tgz(r-4.4-emscripten)scAnnotatR_1.9.2.tgz(r-4.3-emscripten)
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')) |
Bug tracker:https://github.com/grisslab/scannotatr/issues
- tirosh_mel80_example - A Seurat Object Sample
On BioConductor:scAnnotatR-1.11.0(bioc 3.20)scAnnotatR-1.10.0(bioc 3.19)
Last updated 2 months agofrom:77000fc0db
Exports:caret_modelcell_typecell_type<-classify_cellsdelete_modelload_modelsmarker_genesp_thresp_thres<-parentplant_treeplot_roc_curvesave_new_modelscAnnotatRshowtest_classifiertrain_classifier
Dependencies:abindAnnotationDbiAnnotationHubapeaskpassbase64encBHBiobaseBiocFileCacheBiocGenericsBiocManagerBiocVersionBiostringsbitbit64bitopsblobbslibcachemcaretcaToolsclasscliclockclustercodetoolscolorspacecommonmarkcowplotcpp11crayoncrosstalkcurldata.tabledata.treeDBIdbplyrDelayedArraydeldirdiagramdigestdotCall64dplyrdqrnge1071ellipsisevaluatefansifarverfastDummiesfastmapfilelockfitdistrplusFNNfontawesomeforeachfsfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelggridgesglobalsgluegoftestgowergplotsgridExtragtablegtoolshardhatherehighrhtmltoolshtmlwidgetshttpuvhttricaigraphipredIRangesirlbaisobanditeratorsjquerylibjsonliteKEGGRESTkernlabKernSmoothknitrlabelinglaterlatticelavalazyevalleidenlifecyclelistenvlmtestlubridatemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimeminiUIModelMetricsmunsellnlmennetnumDerivopensslparallellypatchworkpbapplypillarpkgconfigplogrplotlyplyrpngpolyclippROCprodlimprogressrpromisesproxypurrrR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLrecipesreshape2reticulaterlangrmarkdownROCRrpartrprojrootRSpectraRSQLiteRtsneS4ArraysS4VectorssassscalesscattermoresctransformSeuratSeuratObjectshapeshinySingleCellExperimentsitmosourcetoolsspspamSparseArrayspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.utilsSQUAREMstringistringrSummarizedExperimentsurvivalsystensortibbletidyrtidyselecttimechangetimeDatetinytextzdbUCSC.utilsutf8uwotvctrsviridisLitewithrxfunxtableXVectoryamlzlibbioczoo
Introduction to scAnnotatR
Rendered fromclassifying-cells.Rmdusingknitr::rmarkdownon Jun 30 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 Jun 30 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 Jun 30 2024.Last update: 2024-03-21
Started: 2020-11-10
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| caret_model | caret_model |
| cell_type | cell_type cell_type<-,scAnnotatR-method |
| Setter for cell_type. Change cell type of a classifier | cell_type<- |
| Internal functions of scAnnotatR package | balance_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 models | classify_cells |
| Delete model/branch from package | delete_model |
| Load classifiers from databases | load_models |
| marker_genes | marker_genes |
| p_thres | p_thres p_thres<-,scAnnotatR-method |
| Setter for predicting probability threshold | p_thres<- |
| parent | parent |
| Plant tree from list of models | plant_tree |
| Plot roc curve | plot_roc_curve |
| Save a model to the package | save_new_model |
| scAnnotatR class. | scAnnotatR |
| Show object | show,scAnnotatR-method |
| Testing process. | test_classifier test_classifier,scAnnotatR-method |
| A Seurat Object Sample | tirosh_mel80_example |
| Train cell type classifier | train_classifier |