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 Jared Simpson

Hello everyone, our April event will feature Jared Simpson from the Ontario Institute for Cancer Research (OICR).

Date: April 12th
Time: 6pm
Location: BCCRC ground floor lecture theatre. 675 West 10th Avenue, Vancouver BC

Title: Analysis Methods for Nanopore Sequencing Data
Abstract: Over the last four years nanopore-based sequencing instruments have become widely available. The portable MInION instrument can sequence extremely long molecules of DNA, which greatly simplifies de novo genome assembly. However, the data is challenging to analyze because the perturbations of electrical current which reveal the DNA sequence are subtle. In my talk I will discuss my group’s efforts to address these analysis challenges through modeling the electric current signal, leading to software for improved consensus calling, SNP calling and detecting base modifications like 5-methylcytosine. I will also discuss how our software enables novel applications of this technology and our current work on directly characterizing RNA molecules.
Bio: Dr. Jared Simpson is a Principal Investigator at the Ontario Institute for Cancer Research and an Assistant Professor in the Department of Computer Science at the University of Toronto. Jared received his PhD from the University of Cambridge in 2012. Prior to graduate school he wrote the first version of the ABySS genome assembler while working as a computational biologist at the BC Genome Sciences Centre. Jared’s research group focuses on developing new algorithms to analyze large biological data sets including genome assembly, probabilistic modeling of sequencing data, the detection of modified bases and the application of genomics to better understand cancer.

Website: Jared Simpson at OICR

Please note:
Trainees are invited to meet with the VanBUG speaker for open discussion of both science and career paths. This takes place 5:00-5:45pm in either the Boardroom or Lunchroom on the ground floor of the BCCRC


Introductory Speaker:
Emma Graham (MsC Student, Mostafavi lab, UBC)

Title: Many inborn errors of metabolism (IEMs) are amenable to treatment, therefore early diagnosis and treatment is imperative. Despite recent advances, the genetic basis of many metabolic phenotypes remain unknown. For discovery purposes, Whole Exome Sequencing (WES) variant prioritization coupled with clinical and bioinformatics expertise is currently the primary method used to identify novel disease-causing variants, however, causation is often difficult to establish due to the number of plausible variants. Integrated analysis of untargeted metabolomics (UM) and WES or Whole Genome Sequencing (WGS) data is a promising systematic approach for identifying causal variants. In this pilot study, we present an automated bioinformatics approach for the integration of WES with UM data from seven neurometabolic patients with known IEMs and 15 controls; our goal was to identify concordance between genetic and metabolomic dysregulation and illustrate the challenges and successes of combining such large datasets. We found that the efficacy of this approach is intimately associated with the type of protein coded by the causative gene, and the uniqueness of its metabolic signature.
Bio: Emma completed her BSc in Biochemistry and Biophysics at Yale University, and is currently pursuing a MSc degree in the Bioinformatics program. She is originally from Ottawa, Ontario.


Webcast Link:
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