Computational approach to evaluate scRNA-seq data quality and gene body coverage with SkewC

Abugessaisa, Imad; Hasegawa, Akira; Katayama, Shintaro; Kere, Juha; Kasukawa, Takeya

doi:10.1016/j.xpro.2022.102038

STAR Protocols

2023

DOI: 10.1016/j.xpro.2022.102038

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Computational approach to evaluate scRNA-seq data quality and gene body coverage with SkewC

Imad Abugessaisa

Akira Hasegawa

Shintaro Katayama

et al.

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2024

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Cited by 1 publication

References 16 publications

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Impacts of Cell Ranger versions on Chromium gene expression data

Abugessaisa,

Hasegawa,

Walker

et al. 2024

Preprint

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In droplet-based Chromium single cell gene expression data by the 10x Genomics platform, cell barcode calling by Cell Ranger (CR) is a standard pipeline. However, no systematic evaluation of the impact of the released versions of CR on Chromium single cell gene expression data has been conducted. To comprehensively evaluate the impact of CR, we considered six molecular quality criteria, quantified gene expression, and performed downstream analysis for 12 single-cell Chromium gene expression datasets. Each dataset was processed by 10 versions of CR resulting in 180 datasets and a total of 702,493 cell barcodes. We demonstrated that different versions of CR yield different numbers of cell barcodes with significant variation in molecular qualities and average gene expression for the same dataset. Our analysis finds distinction between two diverse categories of cell barcodes: common barcodes called (unmasked) by all versions of CR, and specific barcodes only called (unmasked/masked) by some versions. Surprisingly, we observed variations in molecular quality indices between common cell barcodes when called by different versions of CR. The specific barcodes yield skewed gene body coverage and form distinct clusters at the edges of UMAP plots. The choice of CR version affects scores for quality, average gene expression, clustering results, and top cluster marker genes for each dataset. Our study indicates a demonstrable, quantitative effect on downstream analysis from choice of CR version, resulting in widely different Chromium single cell gene expression data for different CR versions.

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Impacts of Cell Ranger versions on Chromium gene expression data

Abugessaisa,

Hasegawa,

Walker

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

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Computational approach to evaluate scRNA-seq data quality and gene body coverage with SkewC

Cited by 1 publication

References 16 publications

Impacts of Cell Ranger versions on Chromium gene expression data

Impacts of Cell Ranger versions on Chromium gene expression data

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