Package: CDI 1.5.0
CDI: Clustering Deviation Index (CDI)
Single-cell RNA-sequencing (scRNA-seq) is widely used to explore cellular variation. The analysis of scRNA-seq data often starts from clustering cells into subpopulations. This initial step has a high impact on downstream analyses, and hence it is important to be accurate. However, there have not been unsupervised metric designed for scRNA-seq to evaluate clustering performance. Hence, we propose clustering deviation index (CDI), an unsupervised metric based on the modeling of scRNA-seq UMI counts to evaluate clustering of cells.
Authors:
CDI_1.5.0.tar.gz
CDI_1.5.0.zip(r-4.5)CDI_1.5.0.zip(r-4.4)CDI_1.5.0.zip(r-4.3)
CDI_1.5.0.tgz(r-4.4-any)CDI_1.5.0.tgz(r-4.3-any)
CDI_1.5.0.tar.gz(r-4.5-noble)CDI_1.5.0.tar.gz(r-4.4-noble)
CDI_1.5.0.tgz(r-4.4-emscripten)
CDI.pdf |CDI.html✨
CDI/json (API)
NEWS
# Install 'CDI' in R: |
install.packages('CDI', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jichunxie/cdi/issues
- one_batch_matrix - Simulated count matrix from one batch
- one_batch_matrix_celltype - Cell type labels of simulated count matrix from one batch
- one_batch_matrix_label_df - Clustering labels for simulated one-batch single-cell count matrix
- two_batch_matrix - Simulated count matrix from two batches
- two_batch_matrix_batch - Batch labels of simulated count matrix from two batches
- two_batch_matrix_celltype - Cell type labels of simulated count matrix from two batches
- two_batch_matrix_label_df - Clustering labels for simulated two-batch single-cell count matrix
On BioConductor:CDI-1.5.0(bioc 3.21)CDI-1.4.0(bioc 3.20)
singlecellsoftwareclusteringvisualizationsequencingrnaseqcellbasedassays
Last updated 23 days agofrom:82b748630b. Checks:OK: 2 NOTE: 2 WARNING: 3. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 31 2024 |
R-4.5-win | WARNING | Oct 31 2024 |
R-4.5-linux | NOTE | Oct 31 2024 |
R-4.4-win | WARNING | Oct 31 2024 |
R-4.4-mac | NOTE | Oct 31 2024 |
R-4.3-win | WARNING | Oct 31 2024 |
R-4.3-mac | OK | Oct 31 2024 |
Exports:calculate_CDICDI_lineplotcontingency_heatmapfeature_gene_selectionsize_factor
Dependencies:abindaskpassbase64encBHBiobaseBiocGenericsBiocParallelbitopsbslibcachemcaToolscliclustercodetoolscolorspacecommonmarkcowplotcpp11crayoncrosstalkcurldata.tableDelayedArraydeldirdigestdotCall64dplyrdqrngevaluatefansifarverfastDummiesfastmapfitdistrplusFNNfontawesomeformatRfsfutile.loggerfutile.optionsfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelggridgesggsciglobalsgluegoftestgplotsgridExtragtablegtoolsherehighrhtmltoolshtmlwidgetshttpuvhttricaigraphIRangesirlbaisobandjquerylibjsonliteKernSmoothknitrlabelinglambda.rlaterlatticelazyevalleidenlifecyclelistenvlmtestmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimeminiUImunsellnlmeopensslparallellypatchworkpbapplypillarpkgconfigplotlyplyrpngpolyclipprogressrpromisespurrrR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLreshape2reticulaterlangrmarkdownROCRrprojrootRSpectraRtsneS4ArraysS4VectorssassscalesscattermoresctransformSeuratSeuratObjectshinySingleCellExperimentsitmosnowsourcetoolsspspamSparseArrayspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsstringistringrSummarizedExperimentsurvivalsystensortibbletidyrtidyselecttinytexUCSC.utilsutf8uwotvctrsviridisLitewithrxfunxtableXVectoryamlzlibbioczoo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Clustering Deviance Index (CDI) | calculate_CDI |
Clustering Deviation Index. | CDI |
Visualize CDI values via a lineplot | CDI_lineplot |
Heatmap of contingency table | contingency_heatmap |
Select feature genes | feature_gene_selection |
Simulated count matrix from one batch | one_batch_matrix |
Cell type labels of simulated count matrix from one batch | one_batch_matrix_celltype |
Clustering labels for simulated one-batch single-cell count matrix | one_batch_matrix_label_df |
Size factor of each cell | size_factor |
Simulated count matrix from two batches | two_batch_matrix |
Batch labels of simulated count matrix from two batches | two_batch_matrix_batch |
Cell type labels of simulated count matrix from two batches | two_batch_matrix_celltype |
Clustering labels for simulated two-batch single-cell count matrix | two_batch_matrix_label_df |