Bioinformatics Seminars

Bioinformatics Seminar

Time: 10:45am Tuesdays.
Level 7 Seminar Room 2, WEHI1

4 July 2017

A framework for differential expression analysis of single-cell RNA-seq data

Agus Salim
La Trobe University / WEHI Bioinformatics

In this talk, I am going to give an overview of our proposed framework for performing differential expression (DE) analysis using single-cell RNA-seq (scRNA-seq) data. The proposed framework is based on zero-inflated negative binomial (ZINB) distribution. Between-cell differences in the amount of starting materials is modelled using a size factor parameter that act as normalization factor. A common feature in scRNA-seq data is the excess of zero count due to the low capture efficiency. We handle this by performing imputation using an EM algorithm. We demonstrate the potential applicability of our approach using both simulated and real datasets and compare the performance of our approach to other methods for performing DE with scRNA-seq data such as MAST and SCDE.

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