klugerlab. To fix this you can add URL: https://blaserlab.r-universe.dev/DAseq to the package DESCRIPTION file. See also theR-universe documentation.Package: DAseq 1.0.0
DAseq: Detecting regions of differential abundance between scRNA-seq datasets
DA-seq is a multiscale approach for detecting DA subpopulations. In contrast to clustering based approaches, our method can detect DA subpopulations that do not form well separated clusters. For each cell, we compute a multiscale differential abundance score measure. These scores are based on the k nearest neighbors in the transcriptome space for various values of k.
Authors:
DAseq_1.0.0.tar.gz
DAseq_1.0.0.zip(r-4.7)DAseq_1.0.0.zip(r-4.6)DAseq_1.0.0.zip(r-4.5)
DAseq_1.0.0.tgz(r-4.6-any)DAseq_1.0.0.tgz(r-4.5-any)
DAseq_1.0.0.tar.gz(r-4.7-any)DAseq_1.0.0.tar.gz(r-4.6-any)
DAseq_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
DAseq/json (API)
| # Install 'DAseq' in R: |
| install.packages('DAseq', repos = c('https://blaserlab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/klugerlab/daseq/issues
- X.2d.melanoma - T-SNE embedding of the melanoma dataset
- X.label.info - Sample label information
- X.label.melanoma - Cell sample labels of the melanoma dataset
- X.melanoma - Top 10 PCs of the melanoma dataset
Last updated from:b1f58e0028. Checks:7 ERROR, 2 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | ERROR | 153 | ||
| source / vignettes | OK | 227 | ||
| linux-release-x86_64 | ERROR | 186 | ||
| macos-release-arm64 | ERROR | 98 | ||
| macos-oldrel-arm64 | ERROR | 78 | ||
| windows-devel | ERROR | 100 | ||
| windows-release | ERROR | 105 | ||
| windows-oldrel | ERROR | 105 | ||
| wasm-release | OK | 168 |
Exports:addDAslotgetDAcellsgetDAregionplotCellLabelplotCellScoreplotDAsiterunSTGSeuratLocalMarkersSeuratMarkerFinderSTGlocalMarkersSTGmarkerFinderupdateDAcells
Dependencies:abindaskpassbase64encBHbitopsbslibcachemcaretcaToolsclasscliclockclustercodetoolscommonmarkcowplotcpp11crosstalkcurldata.tabledeldirdiagramdigestdotCall64dplyrdqrnge1071evaluatefarverfastDummiesfastmapfitdistrplusFNNfontawesomeforeachfsfuturefuture.applygenericsggplot2ggrepelggridgesglmnetglobalsgluegoftestgowergplotsgridExtragtablegtoolshardhatherehighrhtmltoolshtmlwidgetshttpuvhttricaigraphipredirlbaisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelavalazyevallifecyclelistenvlmtestlubridatemagrittrMASSMatrixmatrixStatsmemoisemimeminiUIModelMetricsnlmennetnumDerivopensslotelparallellypatchworkpbapplypillarpkgconfigplotlyplyrpngpolyclippROCprodlimprogressrpromisesproxypurrrR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppTOMLrecipesreshape2reticulaterlangrmarkdownROCRrpartrprojrootRSpectraRtsneS7sassscalesscattermoresctransformSeuratSeuratObjectshapeshinysitmosourcetoolsspspamsparsevctrsspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.univarspatstat.utilsSQUAREMstringistringrsurvivalsystensortibbletidyrtidyselecttimechangetimeDatetinytextzdbutf8uwotvctrsviridisLitewithrxfunxtableyamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Add DA slot | addDAslot |
| DAseq: Detecting regions of differential abundance between scRNA-seq datasets | DAseq-package DAseq |
| DA-seq Step 1 & Step 2: select DA cells | getDAcells |
| DA-seq Step 3: get DA regions | getDAregion |
| Plot cell labels | plotCellLabel |
| Plot a score for each cell | plotCellScore |
| Plot da site | plotDAsite |
| Run STG | runSTG |
| Find local markers | SeuratLocalMarkers |
| DA-seq Step 4: Seurat marker finder to characterize DA regions | SeuratMarkerFinder |
| STG local markers Run STG to find a set of genes that separate a given DA region from a local subset of cells. | STGlocalMarkers |
| DA-seq Step 4: STG feature selection | STGmarkerFinder |
| Update DA cells | updateDAcells |
| t-SNE embedding of the melanoma dataset | X.2d.melanoma |
| Sample label information | X.label.info |
| Cell sample labels of the melanoma dataset | X.label.melanoma |
| Top 10 PCs of the melanoma dataset | X.melanoma |
