Ontology highlight
ABSTRACT:
SUBMITTER: Fang Z
PROVIDER: S-EPMC6573026 | biostudies-literature | 2019 Mar
REPOSITORIES: biostudies-literature
Cell reports 20190301 11
Identification of human disease signature genes typically requires samples from many donors to achieve statistical significance. Here, we show that single-cell heterogeneity analysis may overcome this hurdle by significantly improving the test sensitivity. We analyzed the transcriptome of 39,905 single islets cells from 9 donors and observed distinct β cell heterogeneity trajectories associated with obesity or type 2 diabetes (T2D). We therefore developed RePACT, a sensitive single-cell analysis ...[more]