Package: miQC
Type: Package
Title: Flexible, probabilistic metrics for quality control of scRNA-seq
        data
Version: 1.19.0
Authors@R: 
    c(person("Ariel", "Hippen", role = c("aut", "cre"),
    email = "ariel.hippen@gmail.com"),
    person("Stephanie", "Hicks", role = c("aut"),
    email = "shicks19@jhu.edu"))
Description: 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.
URL: https://github.com/greenelab/miQC
BugReports: https://github.com/greenelab/miQC/issues
License: BSD_3_clause + file LICENSE
Imports: SingleCellExperiment, flexmix, ggplot2, splines
Suggests: scRNAseq, scater, BiocStyle, knitr, rmarkdown
biocViews: SingleCell, QualityControl, GeneExpression, Preprocessing,
        Sequencing
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.2.1
LazyData: TRUE
Config/pak/sysreqs: zlib1g-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2025-10-29 15:06:48 UTC
RemoteUrl: https://github.com/bioc/miQC
RemoteRef: HEAD
RemoteSha: 08e5f5564eb7fcb26dfa1c363826a4b3fd016467
NeedsCompilation: no
Packaged: 2025-10-30 07:29:41 UTC; root
Author: Ariel Hippen [aut, cre],
  Stephanie Hicks [aut]
Maintainer: Ariel Hippen <ariel.hippen@gmail.com>
Depends: R (>= 3.5.0)
Built: R 4.6.0; ; 2025-10-30 07:32:25 UTC; windows
