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calculateQCMetrics defunct, how to calculate the quality metrics by perCellQCMetrics

Bioinformatics Asked on January 1, 2022

I am trying to follow a tutorial from Sanger institute (from May 2019) on analysis of single cell RNA Seq data. They use calculateQCMetric function to calculate the quality metrics, but I am getting an error message that calculateQCMetric is a deprecated (isSpike function is also deprecated). I want to calculate the quality metrics. Can anyone provide code for getting QCMetric step? I attached the previous defunct code below:

umi <- calculateQCMetrics(
   umi,
   feature_controls = list(
       ERCC = isSpike(umi, "ERCC"), 
        MT = isSpike(umi, "MT")
   )

And I use StupidWolf’s code from this question isSpike function in SingleCellExperiment package is deprecated? to instead isSpike function. I also attached below:

Spikein_names = grep("^ERCC-",rownames(molecules),value=TRUE)
SpikeIn = molecules[Spikein_names,]

g = genes(EnsDb.Hsapiens.v86)
MTgene_names = g[seqnames(g)=="MT"]$gene_id
MTgenes = molecules[rownames(molecules) %in% MTgene_names,]
Have a vector of genes to keep:

keep = setdiff(rownames(molecules),c(SpikeIn,MTgenes))
Then make the single cell object:

sce <- SingleCellExperiment(
assays=list(counts=as.matrix(molecules[keep,])),colData=annotation)
Use altExp to slot in the stuff:

altExp(sce, "spike-in") <- SummarizedExperiment(SpikeIn)
altExp(sce, "MTgenes") <- SummarizedExperiment(MTgenes)

I try the below code, which did not work.

> perCellQCMetrics(sce,
 subsets = list(Spikein_names,MTgene_names),
 flatten = TRUE,
 exprs_values = "counts",
 use_altexps = TRUE)

Thanks in advance.

2 Answers

Ok I have figured it out and I am sharing this in case anyone can get help. I used

sce <-addPerCellQC(sce)

which calculated the QC for all the altexps also and adds them to the colData.

Answered by Abhay on January 1, 2022

It would be helpful if you can provide the error message. Guessing from your codes, it's possible that the alternative experiments weren't set correctly. My suggestion:

altExp(sce, "spike-in") <- SummarizedExperiment(assays=list(counts=as.matrix(SpikeIn)))
altExp(sce, "MTgenes") <- SummarizedExperiment(assays=list(counts=as.matrix(MTgenes)))

If you're using altExp, the subsets argument in perCellQCMetrics is unnecessary in this case.

perCellQCMetrics(sce,
exprs_values="counts",
use_altexps=TRUE)

Answered by mattcwh on January 1, 2022

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