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Depth normalization for single-cell genomics count data

Booeshaghi, A. Sina and Hallgrímsdóttir, Ingileif B. and Gálvez-Merchán, Ángel and Pachter, Lior (2022) Depth normalization for single-cell genomics count data. . (Unpublished)

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Single-cell genomics analysis requires normalization of feature counts that stabilizes variance while accounting for variable cell sequencing depth. We discuss some of the trade-offs present with current widely used methods, and analyze their performance on 526 single-cell RNA-seq datasets. The results lead us to recommend proportional fitting prior to log transformation followed by an additional proportional fitting.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper ItemData/Code
Booeshaghi, A. Sina0000-0002-6442-4502
Hallgrímsdóttir, Ingileif B.0000-0002-4710-0047
Gálvez-Merchán, Ángel0000-0001-7420-8697
Pachter, Lior0000-0002-9164-6231
Additional Information: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 4.0 International license. This version posted May 6, 2022. This project started with an investigation of normalization of orthogonal barcoding tags. We thank John Thompson and Linda Hsieh-Wilson for helpful initial discussions related to that problem. We thank Tara Chari for helpful insights on normalization and clustering. Lambda Moses helped with reviewing the Seurat source code. Data and code availability: All data and code to reproduce the figures and results in the paper are available at Author contributions: A.S.B., and L.P. developed the project idea. A.G.M. pre-processed the datasets. A.S.B. performed the analysis. A.S.B. and A.G.M. compiled the supplementary material. A.S.B. drafted the paper. I.B.H. performed the overdispersion simulation. A.S.B., I.B.H., A.G.M., and L.P. wrote, reviewed, and edited the paper. The authors declare no competing interests.
Record Number:CaltechAUTHORS:20220509-762177400
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Official Citation:Depth normalization for single-cell genomics count data. A. Sina Booeshaghi, Ingileif B. Hallgrímsdóttir, Ángel Gálvez-Merchán, Lior Pachter. bioRxiv 2022.05.06.490859; doi:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:114652
Deposited By: Tony Diaz
Deposited On:09 May 2022 17:00
Last Modified:09 May 2022 17:00

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