SCOTv2: Single-Cell Multiomic Alignment with Disproportionate Cell-Type Representation.

ABSTRACT: Multiomic single-cell data allow us to perform integrated analysis to understand genomic regulation of biological processes. However, most single-cell sequencing assays are performed on separately sampled cell populations, as applying them to the same single-cell is challenging. Existing unsupervised single-cell alignment algorithms have been primarily benchmarked on coassay experiments. Our investigation revealed that these methods do not perform well for noncoassay single-cell experiments when there is disproportionate cell-type representation across measurement domains. Therefore, we extend our previous work-Single Cell alignment using Optimal Transport (SCOT)-by using unbalanced Gromov-Wasserstein optimal transport to handle disproportionate cell-type representation and differing sampl

SUBMITTER: Demetci P 

PROVIDER: S-EPMC9805876 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature