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2022-10 Harriet Dashnow CV (published on my website)
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Harriet Dashnow

Empowering genetic diagnoses through bioinformatics

Salt Lake City, UT

harrietdashnow.com

Updated: Feb 2023

Education

Institution

Degree

Completed

Field of study

The University of Melbourne

PhD

Nov 2019

Bioinformatics

The University of Melbourne

MSc

Dec 2013

Bioinformatics (Dean’s honours)

The University of Melbourne

BSc

Dec 2011

Genetics, Biochemistry and Molecular Biology

The University of Melbourne

BA

Dec 2011

Psychology

Funding

Current:

NIH NGHRI K99/R00 Pathway to Independence Award – USD $1,184,940/5 years, Feb 2023–Jan 2028

Past:

NIH NGHRI T32 in Genomic Medicine – USD $76,196/year, 2022–2023

NIH NHLBI BioData Catalyst Fellowship – USD $69,733, 2020

Australian Genomics Health Alliance PhD top-up scholarship – AUD $10,000/year, 2017-2018

MCRI PhD Top Up Scholarship – AUD $5,000/year, 2015-2018

Australian Postgraduate Award/Research Training Program – ~AUD $26,000/year, 2015-2018

Australasian Genomic Technologies Association Small Grants scheme – AUD $5,000, 2014

Research Summary

Research Experience

Jun 2019 - present

Postdoctoral Research Associate, Aaron Quinlan Lab

Eccles Institute of Human Genetics, The University of Utah, USA

Mar 2015 - Jun 2019

Bioinformatician, Alicia Oshlack Lab

Murdoch Children’s Research Institute, The Royal Children’s Hospital, Melbourne, Australia

Nov - Dec 2015

Visiting Scholar, Daniel McArthur Lab

Broad Institute of MIT and Harvard/Massachusetts General Hospital, Massachusetts, USA

Dec 2013 - Feb 2015

Bioinformatician, Life Science Computation Centre, lead by Andrew Lonie

Melbourne Genomic Health Alliance and Victorian Life Sciences Computation Initiative (now Melbourne Bioinformatics), The University of Melbourne, Australia

Dec 2012 -

Jul 2013

Research Assistant, Kathryn Holt’s Lab

Department of Biochemistry and Molecular Biology, The University of Melbourne, Australia

Nov 2010 - Nov 2011

Undergraduate research placement (UROP), Brodnicki Lab

St Vincent’s Institute, St Vincent’s Hospital, Melbourne, Australia

Jan 2008 - Dec 2010

Technical Assistant, Cell and Gene Therapy (Heidi Peters)

Murdoch Children’s Research Institute, The Royal Children’s Hospital, Melbourne, Australia

Teaching

2021

Teaching Assistant, Advanced Sequencing Technologies & Applications

Cold Spring Harbor Laboratory, New York, USA

2014-present

Instructor and lesson developer. Python, R, Unix, Bash, Git.

The Carpentries (Software Carpentry and Data Carpentry). Australia, USA and India.

2013-2017

Lead demonstrator, Genomics and Bioinformatics (coordinator: Leanne Tilly)

Department of Biochemistry and Molecular Biology, The University of Melbourne, Australia

2011-2013

College tutor (in residence), Genetics, Biochemistry and Molecular Biology

Trinity College and St Hilda’s College, The University of Melbourne, Australia

Awards and Prizes

Australian Bioinformatics and Computational Biology Society - Outstanding PhD thesis 2020

American Society of Human Genetics 2020 - Reviewers’ Choice poster abstract award

COMBINE Symposium, Adelaide 2017 – winner best talk

GeneMappers, Geelong 2017 – winner best student talk

Lorne Genome 2017 – winner student poster prize, invited speaker in the Bioinformatics workshop

International Society for Computational Biology, Boston, USA 2014 - winner best student talk

Selected Presentations

Murdoch Children's Research Institute, Australia, Dec 2022 - invited seminar

University of Utah, Human Genetics: Department Retreat, Nov 2022 - talk

Stanford Genetics Conference on Structural Variants and DNA Repeats 2022 - talk

Undiagnosed Diseases Network Tool Building Coalition, June 2022 - invited seminar

Biology of Genomes 2022, NY, USA - poster

TOPMed Structural Variant Working Group, December 2021 -  invited seminar

BioData Catalyst Quarterly Meeting, December 2021 - invited seminar

American Society of Human Genetics 2020 - poster, Reviewers’ Choice poster abstract award

TOPMed Structural Variant Working Group, July 2020 -  invited seminar

University of Utah, Human Genetics: Research in Progress seminar, June 2020

Biology of Genomes 2020, Virtual - poster

Undiagnosed Diseases Network Tool Building Coalition, February 2020 - invited seminar

Center for Genomic Medicine Symposium, University of Utah, January 2020 - poster

Genome Sciences, University of Washington, December 2019 - invited seminar

Genome Informatics 2019, NY, USA – selected talk

Sanger Institute, Cambridge, UK, March 2018 - invited seminar

Genomics of Rare Disease, Cambridge, UK 2018 – invited international speaker

Big Data Instutute, Oxford, UK, March 2018 - invited seminar

Imperial College, London, UK, March 2018 - invited seminar

Center for Mendelian Genomics, University of Washington, January 2018 - invited seminar

Australian Bioinformatics and Computational Biology Association, Adelaide 2017 – talk

COMBINE Symposium, Adelaide 2017 – winner best talk

GeneMappers, Geelong 2017 – winner best student talk

Lorne Genome 2017 – winner student poster prize, invited speaker in the Bioinformatics workshop

Best Practices in Bioinformatics Training, Brisbane 2016 – invited speaker

Australian Bioinformatics and Computational Biology Association, Brisbane 2016 – talk

ISI-CODATA Bangalore, India 2015 – invited international speaker

International Society for Computational Biology, Boston, USA 2014 - winner best student talk

Service to the Scientific Community

Utah Postdoctoral Association Board - Sr. Chair, Jr. Chair, and Advocacy Committee Chair 2020-present

Australian Bioinformatics and Computational Biology Society Executive Committee - Student Representative 2016-2017

COMBINE (The Australian Bioinformatics and Computational Biology Student Association), President 2015, Vice-President/Secretary 2014, student representative 2016-2017

COMBINE Symposium, Melbourne 2014 and Sydney 2015 - Conference convener

Bio21 Undergraduate Research Opportunities Committee 2011-2014

Selected Publications

For a full list of publications please see my profile on Google Scholar

Pedersen, B. S., Brown, J. M., Dashnow, H., Wallace, A. D., Velinder, M., Tristani-Firouzi, M., ... & Quinlan, A. R. (2021). Effective variant filtering and expected candidate variant yield in studies of rare human disease. NPJ Genomic Medicine, 6(1), 1-8.

Dashnow, H., Pedersen, B. S., Hiatt, L., Brown, J., Beecroft, S. J., Ravenscroft, G., ... & Quinlan, A. R. (2021). STRling: a k-mer counting approach that detects short tandem repeat expansions at known and novel loci. bioRxiv. (In review at Genome Biology)

Georgeson, P., Syme, A., Sloggett, C., Chung, J., Dashnow, H., Milton, M., ... & Pope, B. (2019). Bionitio: demonstrating and facilitating best practices for bioinformatics command-line software. GigaScience, 8(9), giz109.

Dashnow, H., Bell, K. M., Stark, Z., Tan, T. Y., White, S. M., & Oshlack, A. (2019). Pooled-parent exome sequencing to prioritise de novo variants in genetic disease. bioRxiv, 601740.

Dashnow, H., Lek, M., Phipson, B., Halman, A., Sadedin, S., Lonsdale, A., ... & Oshlack, A. (2018). STRetch: detecting and discovering pathogenic short tandem repeat expansions. Genome biology, 19(1), 1-13.

Nunez-Iglesias, J., Van Der Walt, S., & Dashnow, H. (2017). Elegant SciPy: The art of scientific python. " O'Reilly Media, Inc.".

Stark, Z., Dashnow, H., Lunke, S., Tan, T. Y., Yeung, A., Sadedin, S., ... & James, P. A. (2017). A clinically driven variant prioritization framework outperforms purely computational approaches for the diagnostic analysis of singleton WES data. European Journal of Human Genetics, 25(11), 1268-1272.

Lonsdale, A., Sietsma Penington, J., Rice, T., Walker, M., & Dashnow, H. (2016). Ten simple rules for a bioinformatics journal club. PLoS computational biology, 12(1), e1004526.

Sadedin, S. P., Dashnow, H., James, P. A., Bahlo, M., Bauer, D. C., Lonie, A., ... & Thorne, N. P. (2015). Cpipe: a shared variant detection pipeline designed for diagnostic settings. Genome medicine, 7(1), 1-10.

​​Dashnow, H., Tan, S., Das, D., Easteal, S., & Oshlack, A. (2015, December). Genotyping microsatellites in next-generation sequencing data. In Bmc Bioinformatics (Vol. 16, No. 2, pp. 1-2). BioMed Central.

Dashnow, H., Lonsdale, A., & Bourne, P. E. (2014). Ten simple rules for writing a PLOS ten simple rules article. PLoS computational biology, 10(10), e1003858.

Kowsar, Y., Dashnow, H., & Lonie, A. (2014, December). Data Interlocking: Coupling analytics to the data. In 2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing (pp. 696-701). IEEE.

Inouye, M., Dashnow, H., Raven, L. A., Schultz, M. B., Pope, B. J., Tomita, T., ... & Holt, K. E. (2014). SRST2: rapid genomic surveillance for public health and hospital microbiology labs. Genome medicine, 6(11), 1-16.

Buck, N. E., Dashnow, H., Pitt, J. J., Wood, L. R., & Peters, H. L. (2012). Development of transgenic mice containing an introduced stop codon on the human methylmalonyl-CoA mutase locus.

Contributions to Science

The first genome-wide algorithm to detect STR expansions.

During my PhD I developed STRetch, the first algorithm able to detect STR expansions at all annotated STR loci across the genome from short read sequencing data. I demonstrated the ability of this method to detect pathogenic STR expansions and begin to characterize STR variation across the genome. STRetch was instrumental in the discovery of the Baratela-Scott Syndrome XYLT1 STR expansion and has been used to diagnose numerous patients with STR diseases.

Calling novel and reference STR expansions across the genome at scale.

Building on my PhD research, as a Postdoc in Aaron Quinlan’s lab at the University of Utah and in collaboration with Brent Pedersen, I developed STRling (https://github.com/quinlan-lab/STRling), a method to detect STR expansions from short-read sequencing data. It is capable of detecting novel STR expansions: expansions where there is no STR in the reference genome at that position (or a different repeat unit from what is in the reference). It can also detect STR expansions that are annotated in the reference genome in a way that is computationally efficient and can scale to thousands of genomes in the cloud. STRling uses k-mer counting to recover mis-mapped STR reads. It then uses soft-clipped reads to precisely discover the position of the STR expansion in the reference genome. I have already run STRling on almost ten thousand human genomes, including 1000 Genomes, CEPH three-generation families, individuals from TOPMed, and hundreds of families with a rare disease but no genetic diagnosis.

Clinical exome and whole genome sequencing pipelines and variant prioritization.

I worked as a Bioinformatician for the Melbourne Genomic Health Alliance, a project to trial clinical exome sequencing as the standard of care. As part of this project, I contributed to the development of Cpipe, a pipeline for variant detection and genetic diagnosis. I was involved in the initial scoping and testing of this pipeline as well as performing analysis for the first few patient cohorts. Cpipe has since been adopted by a number of diagnostic laboratories and has been instrumental in diagnosing many patients. I had the opportunity to lead and contribute to several other clinical genomics projects during my PhD at the Murdoch Children’s Research Institute. In particular, I deployed and assessed a clinically-driven strategy to prioritize variants from clinical exome sequencing at the Royal Children’s Hospital. We showed that a custom gene list approach outperformed state-of-the-art variant prioritization strategies. With Brent Pedersen and the Quinlan Lab, I then generalized my experience with exome analysis to help develop recommended filtering strategies that can be applied to the majority of exome and whole genome cohorts. We provide a fast filtering tool, slivar, to apply these filters and a language to define additional pedigree-aware custom strategies.

Developed a widely-used method to detect antibiotic resistance genes in microbial sequencing data.

I was a key developer of the bioinformatic tool, SRST2 (https://github.com/katholt/srst2), working with Dr Kathryn Holt at the University of Melbourne. The method quickly and accurately detects microbial antibiotic resistance genes and other critical genetic sequences from high throughput sequencing data of bacterial isolates. It uses competitive alignment and scoring of short reads to a database of known antibiotic resistance genes and other genes that impact microbial pathogenicity. SRST2 is a significant advance over previous slower and less accurate assembly-based methods. SRST2 has since been adopted by public health laboratories across the world and has been cited over 800 times.

Characterized a humanized mouse model of Methylmalonic Aciduria.

As a lab technician in the Cell and Gene Therapy laboratory at the Murdoch Children’s Research Institute, lead by Dr Heidi Peters, I contributed to the characterization of a humanized mouse model of Methylmalonic Aciduria (MMA). MMA is an autosomal recessive disorder that causes severe metabolic acidosis and can result in infant fatality. I developed techniques for metabolite measurement in urine, plasma, and tissue, and characterized genetic lesions using PCR, Sanger sequencing, real-time quantitative PCR, agarose and polyacrylamide gel electrophoresis, bacterial cloning, and DNA isolation. This mouse model was used to develop and test potential MMA therapeutics.

In addition to my scientific contributions, I also strongly believe in contributing to the broader research community through teaching and community outreach. To this end I have volunteered to teach Software and Data Carpentry workshops across Australia, in the US, and in India, to upskill researchers in computational approaches. I have developed lesson materials for general data analysis as well as genomics and RNAseq. I have substantial experience in teaching bioinformatics and genetics at both the undergraduate and graduate levels. I co-authored the book “Elegant SciPy”, which teaches cross-disciplinary approaches to scientific programming. I have also written editorials for PLoS Computational Biology and volunteered on a number of scientific and conference committees (detailed below).

I believe that diversity is key to a successful research community. To that end, I committed to mentoring and supporting women, members of the LGBQT+ community, neurodivergent people, people of colour, and parents. I further commit to making our research spaces, such as conferences, more inclusive of the full spectrum of human diversity.