miQC

This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see miQC.

Flexible, probabilistic metrics for quality control of scRNA-seq data


Bioconductor version: 3.16

Single-cell RNA-sequencing (scRNA-seq) has made it possible to profile gene expression in tissues at high resolution. An important preprocessing step prior to performing downstream analyses is to identify and remove cells with poor or degraded sample quality using quality control (QC) metrics. Two widely used QC metrics to identify a ‘low-quality’ cell are (i) if the cell includes a high proportion of reads that map to mitochondrial DNA encoded genes (mtDNA) and (ii) if a small number of genes are detected. miQC is data-driven QC metric that jointly models both the proportion of reads mapping to mtDNA and the number of detected genes with mixture models in a probabilistic framework to predict the low-quality cells in a given dataset.

Author: Ariel Hippen [aut, cre], Stephanie Hicks [aut]

Maintainer: Ariel Hippen <ariel.hippen at gmail.com>

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

Installation

To install this package, start R (version "4.2") and enter:


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

BiocManager::install("miQC")

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("miQC")
miQC HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews GeneExpression, Preprocessing, QualityControl, Sequencing, SingleCell, Software
Version 1.6.0
In Bioconductor since BioC 3.13 (R-4.1) (3 years)
License BSD_3_clause + file LICENSE
Depends R (>= 3.5.0)
Imports SingleCellExperiment, flexmix, ggplot2, splines
System Requirements
URL https://github.com/greenelab/miQC
Bug Reports https://github.com/greenelab/miQC/issues
See More
Suggests scRNAseq, scater, BiocStyle, knitr, rmarkdown
Linking To
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Depends On Me
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Build Report Build Report

Package Archives

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

Source Package miQC_1.6.0.tar.gz
Windows Binary miQC_1.6.0.zip
macOS Binary (x86_64) miQC_1.6.0.tgz
macOS Binary (arm64) miQC_1.6.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/miQC
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/miQC
Bioc Package Browser https://code.bioconductor.org/browse/miQC/
Package Short Url https://bioconductor.org/packages/miQC/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.16 Source Archive