Package: ADAPTS 1.0.22

ADAPTS: Automated Deconvolution Augmentation of Profiles for Tissue Specific Cells

Tools to construct (or add to) cell-type signature matrices using flow sorted or single cell samples and deconvolve bulk gene expression data. Useful for assessing the quality of single cell RNAseq experiments, estimating the accuracy of signature matrices, and determining cell-type spillover. Please cite: Danziger SA et al. (2019) ADAPTS: Automated Deconvolution Augmentation of Profiles for Tissue Specific cells <doi:10.1371/journal.pone.0224693>.

Authors:Samuel A Danziger

ADAPTS_1.0.22.tar.gz
ADAPTS_1.0.22.zip(r-4.7)ADAPTS_1.0.22.zip(r-4.6)ADAPTS_1.0.22.zip(r-4.5)
ADAPTS_1.0.22.tgz(r-4.6-any)ADAPTS_1.0.22.tgz(r-4.5-any)
ADAPTS_1.0.22.tar.gz(r-4.7-any)ADAPTS_1.0.22.tar.gz(r-4.6-any)
ADAPTS_1.0.22.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
ADAPTS/json (API)

# Install 'ADAPTS' in R:
install.packages('ADAPTS', repos = c('https://sdanzige.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sdanzige/adapts/issues

Datasets:
  • Licenses - Licenses required by Celgene legal
  • LM22 - Leukocyte 22 data matrix
  • MGSM27 - Myeloma Genome Signature Matrix 27

On CRAN:

Conda:

5.93 score 3 stars 1 packages 38 scripts 341 downloads 34 exports 49 dependencies

Last updated from:67507831cb. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE195
source / vignettesOK264
linux-release-x86_64NOTE171
macos-release-arm64NOTE172
macos-oldrel-arm64NOTE147
windows-develNOTE99
windows-releaseNOTE141
windows-oldrelNOTE134
wasm-releaseOK150

Exports:AugmentSigMatrixbuildSeedbuildSpilloverMatcalcAccclustWspillOvercollapseCellTypesestCellCounts.nPassestCellPercentestCellPercent.DCQestCellPercent.DeconRNASeqestCellPercent.nnlsestCellPercent.proportionsInAdmixtureestCellPercent.spillOverestCellPercent.svmdecongetF1mccgetLM22cellsgListFromRFhierarchicalClassifyhierarchicalSplitloadMGSM27loadModMaploopTillConvergencematrixToGenelistmeanResultsmissForest.parplotKappasrankByTremakeLM22pscSampleshrinkByKappashrinkSigMatrixspillToConvergencesplitSCdatatestAllSigMatrices

Dependencies:BiobaseBiocGenericsclassclicodetoolsComICScurldigestdoParalleldoRNGe1071farverforeachgenericsglmnetgluegtableiteratorsitertoolsjsonlitelabelinglatticelifecycleMASSMatrixmissForestnnlspcaMethodspheatmappreprocessCoreproxyquantmodR6randomForestrangerrbibutilsRColorBrewerRcppRcppEigenRdpackrlangrngtoolsscalesshapesurvivalTTRviridisLitextszoo

ADAPTS (Automated Deconvolution Augmentation of Profiles for Tissue Specific cells) Vignette

Rendered fromADAPTS.vignette.html.asisusingR.rsp::asison May 12 2026.

Last update: 2019-10-28
Started: 2019-05-14

ADAPTS Vignette #2: (DEPRECATED) Single Cell Analysis

Rendered fromADAPTS2.vignette.html.asisusingR.rsp::asison May 12 2026.

Last update: 2022-09-07
Started: 2019-10-28

ADAPTS Vignette #3: Building a Better Signature Matrix From Single Cell Data

Rendered fromADAPTS3.vignette.html.asisusingR.rsp::asison May 12 2026.

Last update: 2022-09-07
Started: 2022-09-07

ADAPTS Vignette #4: Build a Single Cell Based Matrix and Test on Independant Data

Rendered fromADAPTS4.vignette.html.asisusingR.rsp::asison May 12 2026.

Last update: 2022-09-07
Started: 2022-09-07

ADAPTS Vignette #5: Automated Repeated Leave-Half-Out Cross-Validation for Robust Accuracy Estimates

Rendered fromADAPTS5.vignette.html.asisusingR.rsp::asison May 12 2026.

Last update: 2022-09-07
Started: 2022-09-07

Readme and manuals

Help Manual

Help pageTopics
Make an augmented signature matrixAugmentSigMatrix
Build a deconvolution seed matrix, add the proportional optionbuildSeed
Build a spillover matrixbuildSpilloverMat
Calculate prediction accuracycalcAcc
Cluster with spilloverclustWspillOver
Collapse cell typescollapseCellTypes
Deconvolve with an n-pass spillover matrixestCellCounts.nPass
Wrapper for deconvolution methodsestCellPercent
DCQ DeconvolutionestCellPercent.DCQ
DeconRNASeq deconvolutionestCellPercent.DeconRNASeq
Non-negative least squares deconvolutionestCellPercent.nnls
WGCNA::proportionsInAdmixture deconvolutionestCellPercent.proportionsInAdmixture
Estimate cell percentage from spilloverestCellPercent.spillOver
SVMDECON deconvolutionestCellPercent.svmdecon
Find out at which iteration the results converge, i.e. the mean results are stable.findConvergenceIter
Get f1 / mccgetF1mcc
LM22 look up tablegetLM22cells
Build a gList using random forestgListFromRF
Hierarchical DeconvolutionhierarchicalClassify
Build hierarchical cell clusters.hierarchicalSplit
Licenses required by Celgene legalLicenses
Leukocyte 22 data matrixLM22
Load MGSM27loadMGSM27
LM22 to xCell LUTloadModMap
Loop testAllSigMatrices until convergenceloopTillConvergence
Make a GSVA genelistmatrixToGenelist
A meta analysis for the results from multiple iterationsmeanResults
Myeloma Genome Signature Matrix 27MGSM27
Use parallel missForest to impute missing values.missForest.par
Plot condition numbersplotKappas
Rank genes for each cell typerankByT
Make an Augmented Signature MatrixremakeLM22p
Build groupSize pools according to cellIDsscSample
Calculate conditions numbers for signature subsetsshrinkByKappa
Shrink a signature matrixshrinkSigMatrix
Spillover to convergencespillToConvergence
Split a single cell dataset into multiple setssplitSCdata
Support vector machine deconvolutionSVMDECON
Generate all the signature matrices one time with the option to leave out half of the data as a test settestAllSigMatrices
SVMDECONV helper functionweightNorm