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calculateQCMetrics defunct, how to calculate the quality metrics by perCellQCMetrics

Bioinformatics Asked by Yach on May 4, 2021

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

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 May 4, 2021

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 May 4, 2021

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