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Andre Sim

Bambu — generating context-aware transcriptomes with Oxford Nanopore long-reads

About Andre Sim

Andre is a post-doc in the Göke Lab at the Genome Institute of Singapore, working on analysing and creating methods for long-read RNA-Seq transcriptome data. He received a bachelor’s with honours at Massey University, New Zealand, and a Ph.D. from Phillips University, Germany, through the Max Planck Graduate School.

Abstract

Long-read RNA-Seq technology allows us to annotate transcriptomes at a level of detail previously not achievable, allowing for the detection of many new transcript isoforms. This new technology comes with its own challenges as we run the risk of over-annotating genomes with transcriptional noise, artifacts, and degradation products. To this end, we developed a machine-learning based classification system to identify true full-length transcripts within long-read RNA-Seq data. Using our tool, we can both adjustably and intuitively improve the precision of novel transcriptome annotations and improve performance of subsequent transcript quantification. 

Andre Sim

Andre Sim

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