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DWLS

0.1.0

Gene Expression Deconvolution Using Dampened Weighted Least Squares

0packages depend
3.5Kdownloads / year
test coverage
13/13checks pass

Overview

About
Maintained by Adriana SistigFirst published 2022-05-241 releasesCRAN page ↗GitHub ↗

The rapid development of single-cell transcriptomic technologies has helped uncover the cellular heterogeneity within cell populations. However, bulk RNA-seq continues to be the main workhorse for quantifying gene expression levels due to technical simplicity and low cost. To most effectively extract information from bulk data given the new knowledge gained from single-cell methods, we have developed a novel algorithm to estimate the cell-type composition of bulk data from a single-cell RNA-seq-derived cell-type signature. Comparison with existing methods using various real RNA-seq data sets indicates that our new approach is more accurate and comprehensive than previous methods, especially for the estimation of rare cell types. More importantly,our method can detect cell-type composition changes in response to external perturbations, thereby providing a valuable, cost-effective method for dissecting the cell-type-specific effects of drug treatments or condition changes. As such, our method is applicable to a wide range of biological and clinical investigations. Dampened weighted least squares ('DWLS') is an estimation method for gene expression deconvolution, in which the cell-type composition of a bulk RNA-seq data set is computationally inferred. This method corrects common biases towards cell types that are characterized by highly expressed genes and/or are highly prevalent, to provide accurate detection across diverse cell types. See: https://www.nature.com/articles/s41467-019-10802-z.pdf for more information about the development of 'DWLS' and the methods behind our functions.

Install

Health

CRAN checks
13OK
Slowest check: 12.2 min · r-devel-linux-x86_64-fedora-gcc
Code health
Yes
Tests · ratio 0.01
not tracked
Coverage
100%
Documentation · exports
None
Vignettes
Yes
README
11
Dependencies · direct
Check history
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-05-10
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-05-03
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-04-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 2 earlier snapshots
  • ERROR2026-04-09
    13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Downloads

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Repository

Repository
5Stars
1Forks
3Open issues
0Open PRs
0Releases

Stars over time

2025-05-13 · 32026-07-07 · 5

Dependencies

Declared dependencies
10 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.5.0
LinkingTo (0)
none
Suggests (2)
testthatMatrix
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Code Composition
R 1,424 (57%)Rd 1,091 (43%)
Code characteristics
Cyclomatic complexity
1.0 median / 10 max
Test cases
2 / 0.01 per code line
Documented parameters
100%

Test coverage

Line coverage

Expression

Tests / Examples

Functions

17 17 exported

Complexity

3 avg / 10 max

Call network

17 nodes / 9 edges

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Lowest coverage

Per-function coverage is not measured for this package yet.

People & History

People (2)
Maintainer (1)
Author, Maintainer
Authors (2)
Author, Maintainer
Release timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.0Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2022-05-24
Total releases
1 / 4 yrs
License
GPL-2 OSI
Minimum R
≥ 3.5.0
Bundled data
145 KB / 1 file
Download size
172 KB
Installed size
not tracked yet
With dependencies
not tracked yet