RT Journal Article
SR Electronic
T1 Normalizing and denoising protein expression data from droplet-based single cell profiling
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.02.24.963603
DO 10.1101/2020.02.24.963603
A1 Matthew P. Mulè
A1 Andrew J. Martins
A1 John S. Tsang
YR 2021
UL http://biorxiv.org/content/early/2021/02/28/2020.02.24.963603.abstract
AB Multimodal single-cell protein and transcriptomic profiling (e.g. CITE-seq) holds promise for comprehensive dissection of cellular heterogeneity, yet protein counts measured by oligo-conjugated-antibody can have substantial noise that masks biological variations. Here we integrated experiments and computational analysis to reveal two major noise sources: protein-specific noise from unbound antibodies and cell-specific noise captured by the shared variance of isotype controls and background protein counts. We provide an open source R package (dsb) to denoise and normalize CITE-seq data based on these findings. (https://cran.r-project.org/web/packages/dsb/index.html).Competing Interest StatementThe authors have declared no competing interest.