Statistical Bioinformatics Seminar: Dr Xueyi Dong (WEHI)

Speaker: Dr Xueyi Dong (WEHI) 

Abstract: The lack of benchmark datasets with inbuilt ground-truth makes it challenging
to compare the performance of existing long-read isoform detection and differential
expression analysis workflows.  Here, we present a benchmark experiment using two human
lung adenocarcinoma cell lines that were each profiled in triplicate together with
synthetic, spliced, spike-in RNAs (“sequins”).  Samples were deeply sequenced on
both Illumina short-read and Oxford Nanopore Technologies long-read platforms.
Alongside the ground-truth available via the sequins, we created in silico mixture
samples to allow performance assessment in the absence of true positives or true
negatives.  Our results show that StringTie2 and bambu outperformed other tools from the
6 isoform detection tools tested, DESeq2, edgeR and limma-voom were best amongst the 5
differential transcript expression tools tested and there was no clear front-runner for
performing differential transcript usage analysis between the 5 tools compared, which
suggests further methods development is needed for this application.  

About the speaker: Dr Xueyi Dong is a postdoctoral research officer in Chen lab in ACRF
Cancer Biology and Stem Cells division, the Walter and Eliza Hall Institute of Medical
Research (WEHI).  She did her undergraduate in Zhejiang University in China, majored in
biology science (2014-2018).  She completed her PhD at WEHI in 2023 under the
supervision of Prof.  Matthew Ritchie, Dr.  Charity Law and Prof.  Gordon Smyth.  Her
current research primarily involves the analysis of spatial transcriptomics data and the
investigation of RNA splicing.  

This event will be held online.  

Zoom: https://uni-sydney.zoom.us/j/84087321707