Dr. Jared Simpson
Mid-Career Investigator
The Simpson lab develops algorithms and software for the analysis of high-throughput sequencing data. The lab, led by Dr. Jared Simpson, works primarily on de novo genome assembly, the detection of somatic mutations in cancer and, most recently, the development of algorithms for nanopore-based sequencers.
External Links
Experience & Education
- Investigator I, OICR
- Doctor of Philosophy, University of Cambridge/Wellcome Trust Sanger Institute
- Computational Biologist, Genome Sciences Centre, BC Cancer Agency
- Software Engineer, Electronic Arts
- Bachelor of Science, Computer Science, University of British Columbia
Current Affiliations
- Mid-Career Investigator, OICR
- Assistant Professor, Department of Computer Science, University of Toronto
Select Publications
- Jain M, Koren S, Miga KH, …, Simpson JT, Loman NJ, Loose M. Nanopore sequencing and assembly of a human genome with ultra-long reads. Nat Biotechnol. 2018; 36(4):338-345.
- Simpson JT, Workman RE, Zuzarte PC, …, Timp W. Detecting DNA cytosine methylation using nanopore sequencing. Nat Methods. 2017; 14(4):407-410.
- Quick J, Loman NJ, Duraffour S, Simpson JT, …, Carroll MW. Real-time, portable genome sequencing for Ebola surveillance. Nature. 2016; 530(7589):228-232.
- Loman NJ, Quick J, Simpson JT. A complete bacterial genome assembled de novo using only nanopore sequencing data. Nat Methods. 2015; 12(8):733-5.
- Simpson JT. Exploring genome characteristics and sequence quality without a reference. Bioinformatics. 2014; 30(9):1228-35.
- Simpson JT, Durbin R. Efficient de novo assembly of large genomes using compressed data structures. Genome Res. 2012; 22(3):549-56.
- Simpson JT, Wong K, Jackman SD, Schein JE, Jones SJ, Birol I. ABySS: a parallel assembler for short read sequence data. Genome Res. 2009; 19(6):1117-23.
See Dr. Simpson’s recent publications on PubMed or on Google Scholar.
Research Areas
Disease Areas
Opportunities to Collaborate
If you’re interested in collaborating with Dr. Simpson, please contact him directly.
Visit OICR’s Collaborative Research Resources directory for more opportunities to collaborate with OICR researchers.
Software
- ABySS: ABySS is a de novo, parallel, paired-end sequence assembler that is designed for short reads
- SGA: SGA is a de novo genome assembler based on the concept of string graphs
- Nanopolish: A nanopore consensus algorithm using a signal-level hidden Markov model
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