scQTLtools

This is the development version of scQTLtools; to use it, please install the devel version of Bioconductor.

An R package for single-cell eQTL analysis and visualization


Bioconductor version: Development (3.21)

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: ), 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")
cisSceQTL:An R package for single-cell eQTL analysis. HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews DifferentialExpression, FunctionalGenomics, GeneExpression, GeneticVariability, Genetics, GenomicVariation, Normalization, Regression, SNP, SingleCell, Software, SystemsBiology, VariantDetection, Visualization
Version 0.99.11
In Bioconductor since BioC 3.21 (R-4.5)
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
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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_0.99.11.tar.gz
Windows Binary (x86_64)
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