HSPH Biostatistics and DFCI Data Science Colloquium
Thursday February 27th at 4pm
HSPH FXB Room G13

Yingxin Lin, PhD
Postdoctoral Associate in the Department of Biostatistics at the Yale School of Public Health

The recent emergence of multi-sample multi-condition single-cell multi cohort studies allows researchers to investigate different cell states. The effective integration of multiple large-cohort studies promises biological insights into cells under different conditions that individual studies cannot provide. In this talk, I will present scMerge2, a scalable algorithm that allows data integration of atlas-scale multi-sample multi-condition single-cell studies. scMerge2 is generalized to enable the merging of millions of cells from single-cell studies generated by various single-cell technologies. Using a large data collection with over five million cells from 1000+ individuals, we demonstrate that the integration of multi-sample multi-condition scRNAseq from multiple cohorts reveals signatures derived from cell-type expression that are more accurate in discriminating disease progression.