PT  - JOURNAL ARTICLE
AU  - Bianca Dumitrascu
AU  - Karen Feng
AU  - Barbara E Engelhardt
TI  - GT-TS: Experimental design for maximizing cell type discovery in single-cell data
AID  - 10.1101/386540
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 386540
4099  - http://biorxiv.org/content/early/2018/08/07/386540.short
4100  - http://biorxiv.org/content/early/2018/08/07/386540.full
AB  - We present the Good-Toulmin like estimator via Thompson sampling, a computational method for iterative experimental design in multi-tissue single-cell RNA-seq (scRNA-seq) data. Given a budget and modeling cell type information across tissues, GT-TS estimates how many cells are required for sampling from each tissue with the goal of maximizing cell type discovery across samples from multiple iterations. In both real and simulated data, we demonstrate the advantages of GT-TS in data collection planning when compared to a random strategy in the absence of experimental design.