SMS scnews item created by Shila Ghazanfar at Tue 3 Oct 2017 1326
Type: Seminar
Distribution: World
Expiry: 10 Oct 2017
Calendar1: 9 Oct 2017 1300-1400
CalLoc1: CPC Seminar Room Level 3
Auth: sheilag@psheilag.pc (assumed)

Statistical Bioinformatics Seminar: Freytag -- Cluster Headache: Comparing Clustering Tools for 10X Single Cell Sequencing Data

The aim of the statistical bioinformatics seminar is to provide a forum for people 
working within the broad area of computation and statistics and their application 
to various aspects of biology to present their work and showcase their ongoing 
projects. It is intended to foster the exchange of ideas and build potential 
collaborations across multiple disciplines.

The seminars will be held at 1:00 pm on Monday in Charles Perkins Centre 
Seminar Room (Level 3, large meeting room). The format of the talk is 30~45 
minutes plus questions.

Monday Oct 9, 2017

Speaker: Saskia Freytag (WEHI)

Title: Cluster Headache: Comparing Clustering Tools for 10X Single Cell Sequencing 

Abstract: The commercially available 10x Genomics protocol to generate droplet-based 
single cell RNA-seq (scRNA-seq) data is enjoying growing popularity among researchers. 
Fundamental to the analysis of such scRNA-seq data is the ability to cluster similar 
or same cells into non-overlapping groups. Many competing methods have been proposed 
for this task, but there is currently little guidance with regards to which method 
offers most accuracy. Answering this question is complicated by the fact that 10x 
Genomics data lack cell labels. Thus in this review, we focused on comparing 
clustering solutions of a dozen methods for three datasets on human peripheral 
mononuclear cells generated with 10x Genomics technology. While clustering solutions 
appeared robust, we found that solutions produced by different methods have little 
in common with each other. They also failed to replicate cell type assignment 
generated with supervised labeling approaches. Furthermore, we demonstrated that 
all clustering methods tested clustered cells to a large degree according to the 
amount of ribosomal RNA in each cell.

About the speaker: Saskia completed her Masters in Statistical Science at University 
College London. After finishing she moved back to Germany, where she completed a 
PhD in Biostatistics in 2014. She then got the opportunity to relocate to Melbourne 
to work as a Post-Doctoral Fellow at the Walter and Eliza Hall Institute in Melanie 
Bahlo’s group. Her research focus is methodological development for the analysis of 
high throughput sequencing data. She is co-founder of R-Ladies and an ambassador 

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