B1699
Title: Quantitative estimation of cell-phenotype associations
Authors: Jun Li - University of Notre Dame (United States) [presenting]
Abstract: The focus is on an interesting problem in single-cell RNA-seq data analysis that could be important for medical research: determining associations between cells and phenotypes such as cancer. SCIPAC is developed, being the first algorithm that quantitatively estimates the association between each cell in single-cell data and a phenotype. SCIPAC also provides a p-value for each association. SCIPAC applies to data with virtually any type of phenotype, and its high accuracy is shown in simulated data. On four real cancerous or noncancerous datasets, insights from SCIPAC help interpret the data and generate new hypotheses.
