RT Journal Article
SR Electronic
T1 Depth normalization for single-cell genomics count data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2022.05.06.490859
DO 10.1101/2022.05.06.490859
A1 A. Sina Booeshaghi
A1 Ingileif B. Hallgrímsdóttir
A1 Ángel Gálvez-Merchán
A1 Lior Pachter
YR 2022
UL http://biorxiv.org/content/early/2022/05/06/2022.05.06.490859.abstract
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.