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.
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
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