Package: SMDIC 0.1.5
SMDIC: Identification of Somatic Mutation-Driven Immune Cells
A computing tool is developed to automated identify somatic mutation-driven immune cells. The operation modes including: i) inferring the relative abundance matrix of tumor-infiltrating immune cells and integrating it with a particular gene mutation status, ii) detecting differential immune cells with respect to the gene mutation status and converting the abundance matrix of significant differential immune cell into two binary matrices (one for up-regulated and one for down-regulated), iii) identifying somatic mutation-driven immune cells by comparing the gene mutation status with each immune cell in the binary matrices across all samples, and iv) visualization of immune cell abundance of samples in different mutation status..
Authors:
SMDIC_0.1.5.tar.gz
SMDIC_0.1.5.zip(r-4.5)SMDIC_0.1.5.zip(r-4.4)SMDIC_0.1.5.zip(r-4.3)
SMDIC_0.1.5.tgz(r-4.4-any)SMDIC_0.1.5.tgz(r-4.3-any)
SMDIC_0.1.5.tar.gz(r-4.5-noble)SMDIC_0.1.5.tar.gz(r-4.4-noble)
SMDIC_0.1.5.tgz(r-4.4-emscripten)SMDIC_0.1.5.tgz(r-4.3-emscripten)
SMDIC.pdf |SMDIC.html✨
SMDIC/json (API)
| # Install 'SMDIC' in R: |
| install.packages('SMDIC', repos = c('https://hanjunwei-lab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/hanjunwei-lab/smdic/issues
- envData - EnvData
- xCell.data - XCell datasets
Last updated 9 months agofrom:14d5cc86ed. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 03 2024 |
| R-4.5-win | OK | Sep 03 2024 |
| R-4.5-linux | OK | Sep 03 2024 |
| R-4.4-win | OK | Sep 03 2024 |
| R-4.4-mac | OK | Sep 03 2024 |
| R-4.3-win | OK | Sep 03 2024 |
| R-4.3-mac | OK | Sep 03 2024 |
Exports:exp2cellgene2cellsummaryGetExampleDataheatmapcellmaf2matrixmutcellsummarymutcorcellplotCoocMutexplotwaterfallsurvcell
Dependencies:abindannotateAnnotationDbiaskpassbackportsbase64encbeachmatBHBiobaseBiocFileCacheBiocGenericsBiocParallelBiocSingularBiostringsbitbit64blobbootbroombslibcachemcarcarDataclassclicodetoolscolorspacecommonmarkcorrplotcowplotcpp11crayoncurldata.tableDBIdbplyrDelayedArrayDelayedMatrixStatsDerivdigestDNAcopydoBydplyre1071evaluateexactRankTestsfansifarverfastmapfilelockfontawesomeformatRfsfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggpubrggrepelggsciggsignifggtextgluegraphgridExtragridtextGSAGSEABaseGSVAgtableHDF5ArrayhighrhtmltoolshttpuvhttrimputeIRangesirlbaisobandjpegjquerylibjsonliteKEGGRESTkm.ciKMsurvknitrlabelinglambda.rlaterlatticelifecyclelme4maftoolsmagickmagrittrmarkdownMASSMatrixMatrixGenericsMatrixModelsmatrixStatsmaxstatmemoisemgcvmicrobenchmarkmimeminqamodelrmunsellmvtnormnlmenloptrnnetnumDerivopensslopenxlsxpbkrtestpheatmappillarpkgconfigplogrpngpolynompracmapreprocessCorepromisesproxypurrrquantregR6rappdirsRColorBrewerRcppRcppEigenrhdf5rhdf5filtersRhdf5libRhtslibrjsonrlangRSQLiterstatixrsvdS4ArraysS4VectorssamrsassScaledMatrixscalesshinyshinyFilesSingleCellExperimentsnowsourcetoolsSparseArraySparseMsparseMatrixStatsSpatialExperimentstringistringrSummarizedExperimentsurvivalsurvminersurvMiscsystibbletidyrtidyselectUCSC.utilsutf8vctrsviridisLitewithrxfunXMLxml2xtableXVectoryamlzipzlibbioczoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Identification of somatic mutation-driven immune cells | SMDIC-package |
| A data.frame of 24 immune cells name from Bindea et al | cell24 |
| A data.frame of 64 immune cells name from xCell method | cell64 |
| envData | cellmatrix envData exp.example mutcell mutmatrix |
| exp2cell | exp2cell |
| gene2cellsummary | gene2cellsummary |
| Get the example data | GetExampleData |
| heatmapcell | heatmapcell |
| A large list of 24 immune cells type-specific gene signatures from Bindea et al | immunelist |
| maf2matrix | maf2matrix |
| mutcellsummary | mutcellsummary |
| mutcorcell | mutcorcell |
| plotCoocMutex | plotCoocMutex |
| plotwaterfall | plotwaterfall |
| survcell | survcell |
| xCell datasets | xCell.data |
