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scQTLtools

This is the development version of scQTLtools; for the stable release version, see scQTLtools.

An R package for single-cell eQTL analysis and visualization


Bioconductor version: Development (3.22)

This package specializes in analyzing and visualizing eQTL at the single-cell level. It can read gene expression matrices or Seurat data, or SingleCellExperiment object along with genotype data. It offers a function for cis-eQTL analysis to detect eQTL within a given range, and another function to fit models with three methods. Using this package, users can also generate single-cell level visualization result.

Author: Xiaofeng Wu [aut, cre, cph] ORCID iD ORCID: 0009-0003-6254-5575 , Xin Huang [aut, cph], Jingtong Kang [com], Siwen Xu [aut, cph]

Maintainer: Xiaofeng Wu <1427972815 at qq.com>

Citation (from within R, enter citation("scQTLtools")):

Installation

To install this package, start R (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("scQTLtools")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("scQTLtools")
scQTLtools: An R package for single-cell eQTL analysis. HTML R Script
Reference Manual PDF

Details

biocViews DifferentialExpression, FunctionalGenomics, GeneExpression, GeneticVariability, Genetics, GenomicVariation, Normalization, Regression, SNP, SingleCell, Software, SystemsBiology, VariantDetection, Visualization
Version 1.1.0
In Bioconductor since BioC 3.21 (R-4.5) (< 6 months)
License MIT + file LICENSE
Depends R (>= 4.4.1.0)
Imports ggplot2 (>= 3.5.1), Matrix (>= 1.7-0), stats (>= 4.4.1), progress (>= 1.2.3), stringr (>= 1.5.1), dplyr (>= 1.1.4), SeuratObject (>= 5.0.2), methods (>= 4.4.1), magrittr (>= 2.0.3), patchwork (>= 1.2.0), DESeq2(>= 1.45.3), VGAM (>= 1.1-11), limma(>= 3.61.9), biomaRt(>= 2.61.3), gamlss (>= 5.4-22), SingleCellExperiment(>= 1.27.2), SummarizedExperiment(>= 1.32.0), GOSemSim(>= 2.31.2)
System Requirements
URL https://github.com/XFWuCN/scQTLtools
Bug Reports https://github.com/XFWuCN/scQTLtools/issues
See More
Suggests BiocStyle, knitr, rmarkdown, org.Hs.eg.db, org.Mm.eg.db, org.Ce.eg.db, org.At.tair.db, testthat (>= 3.2.1.1)
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package scQTLtools_1.1.0.tar.gz
Windows Binary (x86_64) scQTLtools_1.1.0.zip
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/scQTLtools
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scQTLtools
Bioc Package Browser https://code.bioconductor.org/browse/scQTLtools/
Package Short Url https://bioconductor.org/packages/scQTLtools/
Package Downloads Report Download Stats