miQC

DOI: 10.18129/B9.bioc.miQC  

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

Bioconductor version: Release (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>

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")

 

HTML	R Script	miQC
PDF		Reference Manual
Text		NEWS
Text		LICENSE

Details

biocViews	GeneExpression, Preprocessing, QualityControl, Sequencing, SingleCell, Software
Version	1.6.0
In Bioconductor since	BioC 3.13 (R-4.1) (2 years)
License	BSD_3_clause + file LICENSE
Depends	R (>= 3.5.0)
Imports	SingleCellExperiment, flexmix, ggplot2, splines
LinkingTo
Suggests	scRNAseq, scater, BiocStyle, knitr, rmarkdown
SystemRequirements
Enhances
URL	https://github.com/greenelab/miQC
BugReports	https://github.com/greenelab/miQC/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
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