Advantages of Modeling Zero-Inflation in ScRNA-Seq Data

• Activity Number: 453 - Advances on the Analysis of Single-Cell Sequencing Data
• Type: Topic Contributed
• Date/Time: Wednesday, July 31, 2019 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Genomics and Genetics
• Author(s): Davide Risso*
• Companies: University of Padova
• Keywords: single cell; RNA-seq; zero inflation; dimensionality reduction; count data; factor analysis

Abstract

Single-cell RNA sequencing is a novel technique that allows researchers to measure gene expres- sion at the resolution of single cells. Compared to "bulk" measurements, single-cell data show an over-abundance of zero counts, and several statistical models have been proposed to account for this zero inflation. Here, we show that in the context of dimensionality reduction, a negative binomial factor analysis model leads to similar results than its zero-inflated counterpart, with substantial computational savings. However, explicitly testing for the difference in the proportion of extra zeros may help identify interesting genes.