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453 – Advances on the Analysis of Single-Cell Sequencing Data
Advantages of Modeling Zero-Inflation in scRNA-Seq Data
Sponsor: Section on Statistics in Genomics and Genetics
Keywords: single cell, RNA-seq, zero inflation, dimensionality reduction, count data, factor analysis
Davide Risso
University of Padova
Single-cell RNA sequencing is a novel technique that allows researchers to measure gene express- 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.