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The SpliZ generalizes “Percent Spliced In” to reveal regulated splicing at single-cell resolution

Julia Eve Olivieri, Roozbeh Dehghannasiri, Julia Salzman
doi: https://doi.org/10.1101/2020.11.10.377572
Julia Eve Olivieri
1Department of Biochemistry, Stanford University, Stanford, CA 94305
2Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305
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Roozbeh Dehghannasiri
1Department of Biochemistry, Stanford University, Stanford, CA 94305
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Julia Salzman
1Department of Biochemistry, Stanford University, Stanford, CA 94305
3Department of Biomedical Data Science, Stanford University, Stanford, CA 94305
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  • For correspondence: [email protected]
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Abstract

To date, detecting robust single-cell-regulated splicing is viewed as out of reach from droplet based technologies such as 10x Chromium. This prevents the discovery of single-cell-regulated splicing in rare cell types or those that are difficult or impossible to sequence deeply. Here, we introduce a novel, robust, and computationally efficient set of statistics, the Splicing Z Score (SpliZ) and SpliZVD, to detect regulated splicing in single cell RNA-seq including 10x Chromium. The SpliZ(VD) provides annotation-free detection of differentially regulated, complex alternative splicing events. The SpliZ generalizes and increases statistical power compared to the Percent Spliced In (PSI) and mathematically reduces to PSI for simple exon-skipping. We applied the SpliZ to primary human lung cells to discover hundreds of genes with new regulated cell-type-specific splicing. The SpliZ has wide application to enable biological discovery of genes predicted to have functionally significant splicing programs including those regulated in development.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Name of the score changed from SZS to SpliZ; modification of the SpliZ, the SpliZVD, introduced; simulations included to compare SpliZ and SpliZVD to PSI; spermatogenesis analysis removed for space reasons; new method of calculating gene-based p values; Figures 1, 2, and 3 revised.

  • https://github.com/juliaolivieri/SZS_pipeline/

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted March 31, 2021.
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The SpliZ generalizes “Percent Spliced In” to reveal regulated splicing at single-cell resolution
Julia Eve Olivieri, Roozbeh Dehghannasiri, Julia Salzman
bioRxiv 2020.11.10.377572; doi: https://doi.org/10.1101/2020.11.10.377572
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The SpliZ generalizes “Percent Spliced In” to reveal regulated splicing at single-cell resolution
Julia Eve Olivieri, Roozbeh Dehghannasiri, Julia Salzman
bioRxiv 2020.11.10.377572; doi: https://doi.org/10.1101/2020.11.10.377572

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