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Bioconductor version: Release (3.18)
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.
Author: Gabriel Hoffman [aut, cre]
Maintainer: Gabriel Hoffman <gabriel.hoffman at mssm.edu>
Citation (from within R,
enter citation("dreamlet")
):
To install this package, start R (version "4.3") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("dreamlet")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("dreamlet")
HTML | R Script | Dreamlet analysis of single cell RNA-seq |
HTML | R Script | Loading large-scale H5AD datasets |
HTML | mashr analysis following dreamlet | |
HTML | R Script | Modeling continuous cell-level covariates |
HTML | R Script | Testing non-linear effects |
Reference Manual | ||
Text | NEWS |
Follow Installation instructions to use this package in your R session.
Source Package | dreamlet_1.0.0.tar.gz |
Windows Binary | dreamlet_1.0.0.zip |
macOS Binary (x86_64) | |
macOS Binary (arm64) | dreamlet_1.0.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/dreamlet |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/dreamlet |
Bioc Package Browser | https://code.bioconductor.org/browse/dreamlet/ |
Package Short Url | https://bioconductor.org/packages/dreamlet/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.18 | Source Archive |
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