This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see miQC.
Bioconductor version: 3.17
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")
):
To install this package, start R (version "4.3") 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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("miQC")
HTML | R Script | miQC |
Reference Manual | ||
Text | NEWS | |
Text | LICENSE |
biocViews | GeneExpression, Preprocessing, QualityControl, Sequencing, SingleCell, Software |
Version | 1.8.0 |
In Bioconductor since | BioC 3.13 (R-4.1) (2.5 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 |
Follow Installation instructions to use this package in your R session.
Source Package | miQC_1.8.0.tar.gz |
Windows Binary | miQC_1.8.0.zip |
macOS Binary (x86_64) | miQC_1.8.0.tgz |
macOS Binary (arm64) | miQC_1.8.0.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 |
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