PT  - JOURNAL ARTICLE
AU  - Booeshaghi, A. Sina
AU  - Hallgrímsdóttir, Ingileif B.
AU  - Gálvez-Merchán, Ángel
AU  - Pachter, Lior
TI  - Depth normalization for single-cell genomics count data
AID  - 10.1101/2022.05.06.490859
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.05.06.490859
4099  - http://biorxiv.org/content/early/2022/05/06/2022.05.06.490859.short
4100  - http://biorxiv.org/content/early/2022/05/06/2022.05.06.490859.full
AB  - 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.Competing Interest StatementThe authors have declared no competing interest.