Package: EasyCellType 1.9.0
Ruoxing Li
EasyCellType: Annotate cell types for scRNA-seq data
We developed EasyCellType which can automatically examine the input marker lists obtained from existing software such as Seurat over the cell markerdatabases. Two quantification approaches to annotate cell types are provided: Gene set enrichment analysis (GSEA) and a modified versio of Fisher's exact test. The function presents annotation recommendations in graphical outcomes: bar plots for each cluster showing candidate cell types, as well as a dot plot summarizing the top 5 significant annotations for each cluster.
Authors:
EasyCellType_1.9.0.tar.gz
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EasyCellType.pdf |EasyCellType.html✨
EasyCellType/json (API)
| # Install 'EasyCellType' in R: |
| install.packages('EasyCellType', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- cellmarker_tissue - Tissues in CellMarker database.
- clustermole_tissue - Tissues in Clustermole database.
- gene_pbmc - Differential expressed marker genes in 9 clusters.
- panglao_tissue - Tissues in Panglao database.
- pbmc_data - Peripheral Blood Mononuclear Cells (PBMC) data.
On BioConductor:EasyCellType-1.9.0(bioc 3.21)EasyCellType-1.8.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
singlecellsoftwaregeneexpressiongenesetenrichment
Last updated 4 months agofrom:902a85b14e. Checks:1 OK, 7 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Feb 17 2025 |
| R-4.5-win | NOTE | Feb 17 2025 |
| R-4.5-mac | NOTE | Feb 17 2025 |
| R-4.5-linux | NOTE | Feb 17 2025 |
| R-4.4-win | NOTE | Feb 17 2025 |
| R-4.4-mac | NOTE | Feb 17 2025 |
| R-4.3-win | NOTE | Feb 17 2025 |
| R-4.3-mac | NOTE | Feb 17 2025 |
Exports:coremarkerseasyctplot_barplot_dotsummarycelltype
Dependencies:AnnotationDbiapeaplotaskpassbase64encBHBiobaseBiocGenericsBiocManagerBiocParallelBiocStyleBiostringsbitbit64blobbookdownbslibcachemcliclusterProfilercodetoolscolorspacecowplotcpp11crayoncurldata.tableDBIdigestDOSEdplyrenrichplotevaluatefansifarverfastmapfastmatchfgseafontawesomeforcatsformatRfsfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataggforceggfunggnewscaleggplot2ggplotifyggrepelggtangleggtreeglueGO.dbGOSemSimgridGraphicsgsongtablehighrhtmltoolshttrigraphIRangesisobandjquerylibjsonliteKEGGRESTknitrlabelinglambda.rlatticelazyevallifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmeopensslorg.Hs.eg.dborg.Mm.eg.dbpatchworkpillarpkgconfigplogrplyrpngpolyclippurrrqvalueR.methodsS3R.ooR.utilsR6rappdirsRColorBrewerRcppRcppEigenreshape2rlangrmarkdownRSQLiteS4VectorssassscalesscatterpiesnowstringistringrsyssystemfontstibbletidyrtidyselecttidytreetinytextreeiotweenrUCSC.utilsutf8vctrsviridisLitewithrxfunXVectoryamlyulab.utils
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Tissues in CellMarker database. | cellmarker_tissue |
| Tissues in Clustermole database. | clustermole_tissue |
| Title Summarize markers contirbuting to the cell type annotation | coremarkers |
| Annotate cell types for scRNA-seq data | easyct |
| Differential expressed marker genes in 9 clusters. | gene_pbmc |
| Title Convert gene symbol to Entrez ID | mapsymbol |
| Tissues in Panglao database. | panglao_tissue |
| Peripheral Blood Mononuclear Cells (PBMC) data. | pbmc_data |
| Create bar plots for each cluster | plot_bar |
| Create dot plot for annotation results | plot_dot |
| Title Annotate cell types for single cell RNA data | process_results |
| Print test results | summarycelltype |
| Fisher exact test used in function 'easyct' | test_fisher |