dreamlet
Bioc currentScalable differential expression analysis of single cell transcriptomics datasets with complex study designs
Release Lineage
Entered 3.18 · Oct 25, 2023
Current · Requires R 4.6
Description
Recent advances in single cell/nucleus transcriptomic technology has enabled collection of cohort-scale datasets to study cell type specific gene expression differences associated disease state, stimulus, and genetic regulation. The scale of these data, complex study designs, and low read count per cell mean that characterizing cell type specific molecular mechanisms requires a user-frieldly, purpose-build analytical framework. We have developed the dreamlet package that applies a pseudobulk approach and fits a regression model for each gene and cell cluster to test differential expression across individuals associated with a trait of interest. Use of precision-weighted linear mixed models enables accounting for repeated measures study designs, high dimensional batch effects, and varying sequencing depth or observed cells per biosample.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
57 22 exported
Complexity
4.9 avg / 43 max
Call network
57 nodes / 45 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
12,596
Files
134
Compiled share
1%
Has compiled src
Yes
Language breakdown
API
Exported functions
35
Internal functions
30
Recent export changes
Testing
Has tests
Yes
Test-to-code ratio
0.00
testthat edition
–
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
–
Unsafe pattern score
0
Dep constraint coverage
7.1%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.3.0
System requirements
1 externalC++11
C++ standard
–
License
Artistic-2.0
License flags
SPDX valid, OSI approved
History
Versions
6
First release
2024-02-27
Latest release
2026-04-28
Avg cadence
161 days
Cold removal rate
100%
Dep drift
4
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 61
- Examples that run
- 100%46 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 95%
- Return-value docs
- 94%
- Help pages citing references
- 5% with a bibliography file
Repository practices
4 development-tooling and community-health practices detected across 2 families in the upstream repository
Checks run against github.com/diseaseneurogenomics/dreamlet on 2026-10-21.
GitHub Pages site last deployed 2026-09-23 · The repository has a site deploy workflow
pkgdown site last built 2026-05-22
Topics
Suggested by (1)
People
- Gabriel Hoffman author maintainer
Cite
Cite this package
Run in R for the authors' entry:
citation("dreamlet")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1101/2023.03.17.533005.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.