Package: scGPS 1.19.0
scGPS: A complete analysis of single cell subpopulations, from identifying subpopulations to analysing their relationship (scGPS = single cell Global Predictions of Subpopulation)
The package implements two main algorithms to answer two key questions: a SCORE (Stable Clustering at Optimal REsolution) to find subpopulations, followed by scGPS to investigate the relationships between subpopulations.
Authors:
scGPS_1.19.0.tar.gz
scGPS_1.19.0.zip(r-4.5)scGPS_1.19.0.zip(r-4.4)scGPS_1.19.0.zip(r-4.3)
scGPS_1.19.0.tgz(r-4.4-x86_64)scGPS_1.19.0.tgz(r-4.3-x86_64)
scGPS_1.19.0.tar.gz(r-4.5-noble)scGPS_1.19.0.tar.gz(r-4.4-noble)
scGPS_1.19.0.tgz(r-4.4-emscripten)scGPS_1.19.0.tgz(r-4.3-emscripten)
scGPS.pdf |scGPS.html✨
scGPS/json (API)
NEWS
# Install 'scGPS' in R: |
install.packages('scGPS', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/imb-computational-genomics-lab/scgps/issues
- day_2_cardio_cell_sample - One of the two example single-cell count matrices to be used for training 'scGPS' model
- day_5_cardio_cell_sample - One of the two example single-cell count matrices to be used for 'scGPS' prediction
- training_gene_sample - Input gene list for training 'scGPS', e.g. differentially expressed genes
On BioConductor:scGPS-1.19.0(bioc 3.20)scGPS-1.18.0(bioc 3.19)
Last updated 2 months agofrom:f97750b6a6
Exports:annotate_clustersbootstrap_parallelbootstrap_predictioncalcDistcalcDistArmaclusteringclustering_baggingCORE_baggingCORE_clusteringCORE_subclusterdistvecfind_markersfind_optimal_stabilityfind_stabilitymean_cppnew_scGPS_objectnew_summarized_scGPS_objectPCAplot_COREplot_optimal_COREplot_reducedpredictingPrinComp_cpprand_indexrcpp_Eucl_distance_NotParrcpp_parallel_distancereformat_LASSOsub_clusteringsubset_cppsummary_accuracysummary_deviancesummary_prediction_lassosummary_prediction_ldatop_vartp_cpptrainingtSNEvar_cpp
Dependencies:abindaskpassBHBiobaseBiocGenericsBiocParallelcaretclasscliclockcodetoolscolorspacecpp11crayoncurldata.tableDelayedArrayDESeq2diagramdigestdplyrdynamicTreeCute1071ellipsisfansifarverfastclusterforeachformatRfutile.loggerfutile.optionsfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2glmnetglobalsgluegowergtablehardhathttripredIRangesisobanditeratorsjsonliteKernSmoothlabelinglambda.rlatticelavalifecyclelistenvlocfitlubridatemagrittrMASSMatrixMatrixGenericsmatrixStatsmgcvmimeModelMetricsmunsellnlmennetnumDerivopensslparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcppRcppArmadilloRcppEigenRcppParallelrecipesreshape2rlangrpartS4ArraysS4VectorsscalesshapeSingleCellExperimentsnowSparseArraySQUAREMstringistringrSummarizedExperimentsurvivalsystibbletidyrtidyselecttimechangetimeDatetzdbUCSC.utilsutf8vctrsviridisLitewithrXVectorzlibbioc