Ruth Dolly Johnson


Hi, I am a first-year Computer Science PhD student at the University of California, Los Angeles. I am interested in computational biology, specifically methods development.

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About

I'm orginally from Visalia, CA, and completed my bachelors in Mathematics of Computation at UCLA in 2017. Currently, I work with Bogdan Pasaniuc and Sriram Sankararaman as a computer science PhD student at UCLA.


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Research

Publications

Improved methods for multi-trait fine mapping of pleiotropic risk loci
Gleb Kichaev; Megan Roytman; Ruth Johnson; Eleazar Eskin; Sara; Lindström; Peter Kraft; Bogdan Pasaniuc; Bioinformatics 2016.


(abstract)

Motivation: Genome-wide association studies (GWAS) have identified thousands of regions in the genome that contain genetic variants that increase risk for complex traits and diseases. However, the variants uncovered in GWAS are typically not biologically causal, but rather, correlated to the true causal variant through linkage disequilibrium (LD). To discern the true causal variant(s), a variety of statistical fine-mapping methods have been proposed to prioritize variants for functional validation.

Results: In this work we introduce a new approach, fastPAINTOR, that leverages evidence across correlated traits, as well as functional annotation data, to improve fine-mapping accuracy at pleiotropic risk loci. To improve computational efficiency, we describe an new importance sampling scheme to perform model inference. First, we demonstrate in simulations that by leveraging functional annotation data, fastPAINTOR increases fine-mapping resolution relative to existing methods. Next, we show that jointly modeling pleiotropic risk regions improves fine-mapping resolution compared to standard single trait and pleiotropic fine mapping strategies. We report a reduction in the number of SNPs required for follow-up in order to capture 90% of the causal variants from 23 SNPs per locus using a single trait to 12 SNPs when fine-mapping two traits simultaneously. Finally, we analyze summary association data from a large-scale GWAS of lipids and show that these improvements are largely sustained in real data.

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Presentations

CANVIS: Correlation Annotation VISualization
Ruth Johnson; Gleb Kichaev; Bogdan Pasaniuc
RECOMB-Genetics Satellite Meeting, July 2017. Los Angeles, CA, USA. Short talk.

Leveraging Functional Annotations in Fine-mapping of Causal Variants for Complex Traits
Ruth Johnson; Gleb Kichaev; Kathryn Burch; Bogdan Pasaniuc
UCLA Undergraduate Research Poster Day, May 2017. Los Angeles, CA, USA. Poster presentation.

Visualizing correlated causal variants
Ruth Johnson; Gleb Kichaev; Bogdan Pasaniuc
Annual meeting of the American Society of Human Genetics, October 2016. Vancouver, CN. Poster presentation.

SOHBRIT (Space Object Hyperspectral Bidirectional Reflectance Distribution Function Imaging Telescope)
Ruth Johnson; Connor Hitt; Nick Blazier
Sandia Summer Research Symposium, August 2016. Albuquerque, NM, USA. Poster presentation.

Blog

- Visualizing fine-mapping studies with CANVIS [1/6/18]

- 7 Tips for the Grad School Application Grind[10/21/17]

- Additionally I have a few things written on my Medium account

Articles

Awards and Honors

Resume & CV

Resume
CV

Contact

Email: ruthjohnson at ucla dot edu

Github: ruthjohnson95

Twitter: @ruthie_johnson

LinkedIn: linkedin.com/in/ruthjohnson13/