ADAPTS: Automated Deconvolution Augmentation of Profiles for Tissue Specific Cells

Augments existing or de-novo cell-type signature matrices to deconvolve bulk gene expression data. Useful for building signature matrices from single cell RNAseq data, determine cell type deconvolution spillover, and hierarchical deconvolution to use spillover to increase deconvolution accuracy. Please cite: Danziger SA et al. (2019) ADAPTS: Automated Deconvolution Augmentation of Profiles for Tissue Specific cells <doi:10.1101/633958>. This package expands on the techniques outlined in Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, Hoang CD, Diehn M, Alizadeh, AA (2015) <doi:10.1038/nmeth.3337>'s Nature Methods paper: 'Robust enumeration of cell subsets from tissue expression profiles' to allow a user to easily add their own cell types (e.g. a tumor specific cell type) to Newman's LM22 or other signature matrix.

Version: 0.9.26
Depends: R (≥ 3.3.0)
Imports: missForest, e1071, WGCNA, ComICS, pheatmap, doParallel, quantmod, preprocessCore, pcaMethods, foreach, DeconRNASeq, nnls
Suggests: R.rsp
Published: 2019-10-29
Author: Samuel A Danziger
Maintainer: Samuel A Danziger <sam.danziger at>
License: MIT + file LICENSE
Copyright: Celgene Corporation
NeedsCompilation: no
Materials: README
CRAN checks: ADAPTS results


Reference manual: ADAPTS.pdf
Vignettes: ADAPTS (Automated Deconvolution Augmentation of Profiles for Tissue Specific cells) Vignette
ADAPTS Vignette #2: Single Cell Analysis
Package source: ADAPTS_0.9.26.tar.gz
Windows binaries: r-prerelease:, r-release:, r-oldrel:
macOS binaries: r-prerelease: not available, r-release: not available, r-oldrel: not available
Old sources: ADAPTS archive


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