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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
Abstract #304106 Presentation
Title: Advantages of Modeling Zero-Inflation in ScRNA-Seq Data
Author(s): Davide Risso*
Companies: University of Padova
Keywords: single cell; RNA-seq; zero inflation; dimensionality reduction; count data; factor analysis

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.

Authors who are presenting talks have a * after their name.

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