qc: Quality control annotation

qcR Documentation

Quality control annotation

Description

A dataset containing the the quality control of single-cell data. The Y matrix and QC matrix are quite similar. I like to think that Y are specific experimental phenotypes that one would like to gain biological insights into. QC is more adequate for technical variation, weather from manipulation and batch processing of samples, and/or biological such as expected ploidy from flow cytometry indexed FCS file.

I think that good QC data is a reflection of good laboratory notes, and practices. They can provide additional support to make decisions such as including or excluding certain samples. Hence why it's a required parameter in the CNR.

Usage

data(qc)

Format

A data frame n.cell rows x qc.metrics columns

  • cellID, single-cell ID as the rownames ! this is imperative or it will be re-written by the function

  • ReadsKept, Number of reads kept after alignment

  • MedianBinCount, Median number of reads per bin

  • dna.ng.ul, DNA concentration of the cell post amplification

  • sort.gate, 2N, 3N, or 4N gate sorted in FACS. Sets expected value of ploidy. Not required but highly recomended

  • qc.status, binary or multinomial PASS/FAIL/WARNING call for each cell; it's based on your criteria, though some recomendations are provided in the use vignette

Source

https://github.com/SingerLab/GAC


SingerLab/gac documentation built on Oct. 14, 2022, 4:09 a.m.