Package: dreamlet
Type: Package
Title: Scalable differential expression analysis of single cell
        transcriptomics datasets with complex study designs
Version: 1.7.1
Date: 2025-04-24
Authors@R: person("Gabriel", "Hoffman", role=c("aut", "cre"), email="gabriel.hoffman@mssm.edu", comment=c(ORCID="0000-0002-0957-0224"))
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.
VignetteBuilder: knitr
License: Artistic-2.0
Encoding: UTF-8
URL: https://DiseaseNeurogenomics.github.io/dreamlet
BugReports: https://github.com/DiseaseNeurogenomics/dreamlet/issues
Suggests: BiocStyle, knitr, pander, rmarkdown, muscat, ExperimentHub,
        RUnit, muscData, scater, scuttle
biocViews: RNASeq, GeneExpression, DifferentialExpression, BatchEffect,
        QualityControl, Regression, GeneSetEnrichment, GeneRegulation,
        Epigenetics, FunctionalGenomics, Transcriptomics,
        Normalization, SingleCell, Preprocessing, Sequencing,
        ImmunoOncology, Software
Depends: R (>= 4.3.0), variancePartition (>= 1.36.1),
        SingleCellExperiment, ggplot2
Imports: edgeR, SummarizedExperiment, DelayedMatrixStats,
        sparseMatrixStats, MatrixGenerics, Matrix, methods, purrr,
        GSEABase, data.table, zenith (>= 1.1.2), mashr (>= 0.2.52),
        ashr, dplyr, BiocParallel, ggbeeswarm, S4Vectors, IRanges,
        irlba, limma, metafor, remaCor, broom, tidyr, rlang,
        BiocGenerics, S4Arrays, SparseArray, DelayedArray, gtools,
        reshape2, ggrepel, scattermore, Rcpp, lme4 (>= 1.1-33), MASS,
        Rdpack, utils, stats
RoxygenNote: 7.3.2
RdMacros: Rdpack
SystemRequirements: C++11
LinkingTo: Rcpp, beachmat
git_url: https://git.bioconductor.org/packages/dreamlet
git_branch: devel
git_last_commit: 2af7734
git_last_commit_date: 2025-04-24
Repository: Bioconductor 3.22
Date/Publication: 2025-10-07
NeedsCompilation: yes
Packaged: 2025-10-07 21:33:59 UTC; biocbuild
Author: Gabriel Hoffman [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-0957-0224>)
Maintainer: Gabriel Hoffman <gabriel.hoffman@mssm.edu>
Built: R 4.6.0; x86_64-w64-mingw32; 2025-10-29 21:06:26 UTC; windows
Archs: x64
