Kylee Degatano
Pomfret, Connecticut, United States
Summary
🤩
Rockstar🎓
Top SchoolKylee Degatano is a staff product manager specializing in multi-omics with 11 years of hands-on experience spanning sequencing at the bench, software engineering for computational biology, and production CLIA genomics pipelines. She has led large-scale genomics products at the Broad Institute—driving the Genomic Variant Store, WARP pipelines, and HCA analysis services—and currently applies that domain expertise to multi-omics product strategy at Recursion. Known for bridging scientists and engineers, she translates complex research requirements into scalable, cost-optimized cloud pipelines and reproducible workflows used by global consortia. An active contributor to Picard, she’s improved core sequencing QC tooling (notably GC bias metrics), reflecting a rare combination of production genomics operations and open-source impact. Colleagues rely on her to reduce runtime and cloud spend while delivering validated, CLIA-ready analysis for population-scale projects.
11 years of coding experience
12 years of employment as a software developer
BSE Engineering Science Biotechnology Computer Science, BSE Engineering Science Biotechnology Computer Science at Tufts UniversityNone Software Engineering, None Software Engineering at Harvard Extension SchoolWoodstock AcademyBioinformatics, Bioinformatics at Boston University
Spanish
Github Skills (14)
testing10
bioinformatics10
javas10
cra10
bam10
java10
sam10
data-analysis9
data-structure9
performance-optimization9
data-structures9
algorithm9
algorithms9
python4
Programming languages (11)
Github contributions (5)
broadinstitute/picard
Mar 2015 - Aug 2016
A set of command line tools (in Java) for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 review, 45 commits, 43 PRs in 1 year 5 months
Contributions summary:Kylee primarily contributed to the `CollectGcBiasMetrics` tool, modifying its functionality and improving its accuracy. The changes included refactoring the code to work as a `SinglePassSamProgram` and a `MultiLevelCollector`, adding tests, and addressing issues such as double-counting and memory usage. Additionally, the user incorporated new metrics and addressed edge cases, such as empty intervals and large datasets, ensuring robustness and performance.
sequencebamcramcommand-line-toolsfasta
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