Low Fraction Reads in Cells (Cellranger Count Pipeline)
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Entering edit mode
5 months ago
Cricket ▴ 10

I just finished running some single nucleus rna seq fastq files through Cellranger's count pipeline and I received this warning:

Low Fraction Reads in Cells 67.0% Ideal > 70%. Application performance may be affected. Many of the reads were not assigned to cell-associated barcodes. This could be caused by high levels of ambient RNA or by a significant population of cells with a low RNA content, which the algorithm did not call as cells. The latter case can be addressed by inspecting the data to determine the appropriate cell count and using --force-cells.

There are 6 samples and all of them have low fraction reads (~54%-67%). Here is the call format:

cellranger count --id=A1 --fastqs=data/sample_data/fastqs/A1_S1_L001 --sample=A1 --transcriptome=data/reference_data/cellranger_ref_data/mouse_mm10-3.0.0 --include-introns --localmem=128 --localcores=32

This is my first time working with snRNA-seq data and it is not clear to me if this is typical for single nucleus data or if there was something that happened during library prep/isolation/sequencing processes. Any guidance or suggestions/thoughts are _greatly_ appreciated, thank you in advance. Here is an image of a summary file

snRNA-seq 10X cellranger • 716 views
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Entering edit mode
4 months ago

I'd be much more worried if it were an "error" instead of a "warning", and you're very close to the cutoff for the warning too. (see https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/troubleshooting#alerts).

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Entering edit mode
4 months ago

I did 28 Sn-RNA sequencing in human brain and in none of my web summaries I got this error as the fraction read in cell were almost more than 80%. However, I got other errors like "High Fraction of Reads Mapped Antisense to Genes". I also applied --force cell option to retrieve more cells. But the median gene per cell and the number of MT genes in those cells retrieved by Cellranger had decrease and increase in number respectively. So, you can also try it. FYI, I'm aware that in SnRNA seq we should not have MT gene but it usually happen. I'm not sure what region you sequenced. But considering high number of read per cell which is reasonable the number of genes are low. So, it could refer to the type of cells you sequenced. You should have an idea of the population you sequenced. I think the saturation should be more than 50 in your case right? Hope it helps! Paria

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