Dr. Robin Coope
Instrumentation Group Leader
Robin Coope is the Instrumentation Group Leader at the BC Cancer Agency's Genome Sciences Centre and has been in the genomics field since 2000. In this position Dr. Coope is responsible for evaluating new instrumentation as well as designing de-novo solutions. He holds a BASc and MASc in Engineering Physics and a PhD in Physics from the University of British Columbia.
Research Focus
Dr. Coope’s team is responsible for operating liquid-handling robots for high throughput sample preparation for genomics, evaluating and implementing new genomics technologies such as the Oxford Nanopore MinION, and developing de-novo devices where needed. An example of the latter is a 96 channel size selection robot for NGS sample preparation that has been licensed and commercialized by Coastal Genomics based in Burnaby, BC. Dr. Coope is also involved in a variety of biomedical device projects. He has published on solid state physics, display research and genome and biology and technology.
Example Project
"Enriching the Tumour Fraction of Biopsied Tissue for Genomic Analysis”
A challenge in clinical sequencing is to make genetic testing of tumour tissue affordable and timely at large scale. Great strides have been made in reducing sequencing costs and automating both sample preparation and the analysis of sequencing data. A technology which will further improve this analysis is to enrich for tumour material in the samples going into sequencing from tissue biopsies, particularly for whole genome and transcriptome sequencing. Higher tumour content relative to background normal material improves the accuracy and confidence of genomic and gene expression analysis and can lower sequencing costs as less depth of coverage is required. Enrichment has been demonstrated on sections of fixed tissue using conventional laser microdissection with a novel semi-automated system for mapping regions of interest across the slide and exporting that map to the dissection instrument. A new and much faster system for laser dissection is now in development based on industrial engraving equipment coupled with specific slide coatings. This should allow for sufficient quantities of tumour to be obtained for sequencing from tissue sections in minutes. The remaining issue in scaling this process is automating the recognition of tumour sites across a section. This is an ideal problem for machine learning, but the challenge will be obtaining training data which would consist of annotated slides of different tumour types. Since such training sets do not currently exist, this obtaining them, particularly by partnering with clinical pathologists, has become a focus.
Research Keywords
Clinical and Research Lab Instrumentation, Medical Devices, High Throughput Genomics
