recipe bioconductor-miqc

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

Homepage

https://bioconductor.org/packages/3.14/bioc/html/miQC.html

License

BSD_3_clause + file LICENSE

Recipe

/bioconductor-miqc/meta.yaml

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.

package bioconductor-miqc

Versions

1.2.0-0,  1.0.0-0

Depends

• bioconductor-singlecellexperiment >=1.16.0,<1.17.0

• r-base >=4.1,<4.2.0a0

• r-flexmix

• r-ggplot2

Required By

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-miqc

and update with:

conda update bioconductor-miqc

or use the docker container:

docker pull quay.io/biocontainers/bioconductor-miqc:<tag>

(see bioconductor-miqc/tags for valid values for <tag>)

Download stats

Link to this page

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-miqc/README.html)