Package: conos 1.5.4
conos: Clustering on Network of Samples
Wires together large collections of single-cell RNA-seq datasets, which allows for both the identification of recurrent cell clusters and the propagation of information between datasets in multi-sample or atlas-scale collections. 'Conos' focuses on the uniform mapping of homologous cell types across heterogeneous sample collections. For instance, users could investigate a collection of dozens of peripheral blood samples from cancer patients combined with dozens of controls, which perhaps includes samples of a related tissue such as lymph nodes. This package interacts with data available through the 'conosPanel' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/conos>. The size of the 'conosPanel' package is approximately 12 MB.
Authors:
conos_1.5.4.tar.gz
conos_1.5.4.zip(r-4.7)conos_1.5.4.zip(r-4.6)conos_1.5.4.zip(r-4.5)
conos_1.5.4.tgz(r-4.6-x86_64)conos_1.5.4.tgz(r-4.6-arm64)conos_1.5.4.tgz(r-4.5-x86_64)conos_1.5.4.tgz(r-4.5-arm64)
conos_1.5.4.tar.gz(r-4.7-arm64)conos_1.5.4.tar.gz(r-4.7-x86_64)conos_1.5.4.tar.gz(r-4.6-arm64)conos_1.5.4.tar.gz(r-4.6-x86_64)
conos_1.5.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
conos/json (API)
| # Install 'conos' in R: |
| install.packages('conos', repos = c('https://kharchenkolab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/kharchenkolab/conos/issues
- small_panel.preprocessed - Small pre-processed data from Pagoda2, two samples, each dimension
batch-correctionscrna-seqsingle-cell-rna-seqopenblascppopenmp
Last updated from:e656464d70. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 385 | ||
| linux-devel-x86_64 | OK | 469 | ||
| source / vignettes | OK | 350 | ||
| linux-release-arm64 | OK | 410 | ||
| linux-release-x86_64 | OK | 429 | ||
| macos-release-arm64 | OK | 252 | ||
| macos-release-x86_64 | OK | 575 | ||
| macos-oldrel-arm64 | OK | 266 | ||
| macos-oldrel-x86_64 | OK | 504 | ||
| windows-devel | OK | 774 | ||
| windows-release | OK | 344 | ||
| windows-oldrel | OK | 696 | ||
| wasm-release | OK | 308 |
Exports:basicSeuratProcbestClusterThresholdsbestClusterTreeThresholdsbuildWijMatrixConosconvertToPagoda2edgeMatedgeMat<-embeddingPlotestimateWeightEntropyPerCellfindSubcommunitiesgetBetweenCellTypeCorrectedDEgetBetweenCellTypeDEgetCellNamesgetClusteringgetCountMatrixgetEmbeddinggetGeneExpressiongetGenesgetOverdispersedGenesgetPcagetPerCellTypeDEgetRawCountMatrixgetSampleNamePerCellgreedyModularityCutleiden.communityp2app4conosplotClusterBarplotsplotClusterBoxPlotsByAppTypeplotComponentVarianceplotDEheatmapprojectKNNsrawMatricesWithCommonGenessaveConosForScanPysaveDEasCSVsaveDEasJSONscanKModularitysgdBatchesstableTreeClustersvelocityInfoConos
Dependencies:abindBHBiocGenericsbrewcirclizecliclueclustercodetoolscolorspaceComplexHeatmapcowplotcpp11crayondendextenddendsortdigestdoParalleldplyrdqrngdratfarverfastclusterFNNforeachgenericsGetoptLongggplot2ggrepelGlobalOptionsgluegridExtragtableigraphIRangesirlbaisobanditeratorslabelinglatticeleidenAlglifecyclemagrittrMASSMatrixmatrixStatsmgcvN2Rnlmepagoda2pbmcapplypillarpkgconfigplyrpngpROCR.methodsS3R.ooR.utilsR6RColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppProgressRcppSpdlogreshape2rjsonrlangRMTstatRookRSpectraRtsneS4VectorsS7scalessccoreshapesitmostringistringrtibbletidyselecttriebeardurltoolsutf8uwotvctrsviridisviridisLitewithr
