Automated Deconvolution Augmentation of Profiles for Tissue Specific Cells
Overview
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.
Install
Health
NOTERd filesr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64
checkRd: (-1) SVMDECON.Rd:23: Lost braces; missing escapes or markup?
23 | and the best result from three values of v = {0.25, 0.5, 0.75}
| ^NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Samuel A Danziger <sam.danziger@gmail.com>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: person(given = c("Samuel", "A"),
family = "Danziger",
role = c("aut", "cre"),
email = "sam.danziger@gmail.com")
as necessary.- NOTE13 NOTENow
- NOTE14 NOTE2026-03-13
- ERROR13 NOTE, 1 ERROR2026-03-12
- NOTE14 NOTE2026-03-10
Documentation
- Help pages
- 40
- Examples that run
- 94%33 run in a plain check · 2 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 94%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
- ADAPTS (Automated Deconvolution Augmentation of Profiles for Tissue Specific cells) Vignette HTML
- ADAPTS Vignette #2: (DEPRECATED) Single Cell Analysis HTML
- ADAPTS Vignette #3: Building a Better Signature Matrix From Single Cell Data HTML
- ADAPTS Vignette #4: Build a Single Cell Based Matrix and Test on Independant Data HTML
- ADAPTS Vignette #5: Automated Repeated Leave-Half-Out Cross-Validation for Robust Accuracy Estimates HTML
Downloads
Dependencies
Installing ADAPTS adds 38 packages (19 with compiled code, 19 MB of source tarballs). Heaviest: glmnet 2.7 MB, Rcpp 1.8 MB, RcppEigen 1.7 MB. 2 more not on CRAN are not measured.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 1.0.22Latest
- RR 4.2.0 released · 2022-04-22
- 1.0.21
- RR 4.1.0 released · 2021-05-18
- 1.0.6
- 1.0.5
- 1.0.32020-08-06 · diff ↗ ·
added 9 exports
buildSeed, calcAcc, gListFromRF, getF1mcc, plotKappas, scSample, shrinkByKappa, shrinkSigMatrix, splitSCdata - RR 4.0.0 released · 2020-04-24
- 0.9.26
- 0.9.212019-08-07 · diff ↗
- 0.9.202019-06-18 · diff ↗ ·
removed 2 exports
heirarchicalClassify, heirarchicalSplitadded 3 exports
estCellPercent.nnls, hierarchicalClassify, hierarchicalSplit - 0.9.142019-05-17
Show 1 earlier eventHide 1 earlier event
- RR 3.6.0 released · 2019-04-26
Package metadata
- First published
- 2019-05-17
- Total releases
- 9 / 7 yrs
- License
- MIT + file LICENSE OSI
- Copyright
- Bristol-Myers Squibb
- Minimum R
- ≥ 3.3.0
- Bundled data
- 188 KB / 3 files
- Download size
- 4.6 MB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("ADAPTS")Cite the R Observatory
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