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>.

Version: 1.0.22
Depends: R (≥ 3.3.0)
Imports: missForest, e1071, ComICS, pheatmap, doParallel, utils, quantmod, preprocessCore, pcaMethods, foreach, nnls, ranger
Suggests: R.rsp, DeconRNASeq, WGCNA
Published: 2022-09-14
DOI: 10.32614/CRAN.package.ADAPTS
Author: Samuel A Danziger
Maintainer: Samuel A Danziger <sam.danziger at>
License: MIT + file LICENSE
Copyright: Bristol-Myers Squibb
NeedsCompilation: no
Materials: README
In views: Omics
CRAN checks: ADAPTS results


Reference manual: ADAPTS.pdf
Vignettes: ADAPTS (Automated Deconvolution Augmentation of Profiles for Tissue Specific cells) Vignette
ADAPTS Vignette #2: (DEPRECATED) Single Cell Analysis
ADAPTS Vignette #3: Building a Better Signature Matrix From Single Cell Data
ADAPTS Vignette #4: Build a Single Cell Based Matrix and Test on Independant Data
ADAPTS Vignette #5: Automated Repeated Leave-Half-Out Cross-Validation for Robust Accuracy Estimates


Package source: ADAPTS_1.0.22.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): ADAPTS_1.0.22.tgz, r-oldrel (arm64): ADAPTS_1.0.22.tgz, r-release (x86_64): ADAPTS_1.0.22.tgz, r-oldrel (x86_64): ADAPTS_1.0.22.tgz
Old sources: ADAPTS archive

Reverse dependencies:

Reverse imports: scMappR


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