Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model

Volume: 20, Issue: 1
Published: Dec 1, 2019
Abstract
Single-cell RNA-Seq (scRNA-Seq) profiles gene expression of individual cells. Recent scRNA-Seq datasets have incorporated unique molecular identifiers (UMIs). Using negative controls, we show UMI counts follow multinomial sampling with no zero inflation. Current normalization procedures such as log of counts per million and feature selection by highly variable genes produce false variability in dimension reduction. We propose simple multinomial...
Paper Details
Title
Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model
Published Date
Dec 1, 2019
Volume
20
Issue
1
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