Granger Sutton
Data Scientist, National Cancer Institute, CBIIT, Data Ecosystems Branch
Rockville, Maryland, United States
Summary
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Senior🎓
Top SchoolGranger Sutton is a seasoned bioinformatics and genomics leader with 19 years of experience steering large-scale sequencing, assembly, and comparative genomics efforts, now serving as a Data Scientist at the National Cancer Institute. He has led prokaryotic informatics and software engineering at JCVI, co-developed pan-genome pipelines and contributed to high-impact projects like the Human Microbiome and Global Ocean Survey. A pioneer of whole-genome shotgun assembly and a former director at Celera and TIGR, he combines deep algorithmic expertise with hands-on C development—his contributions to the Canu assembler improved clustering and unitig demotion logic. Author of 70+ publications and an experienced PI and manager, he is known for translating complex genomic problems into robust open-source software and scalable analysis pipelines. Based in Rockville, MD, he uniquely blends electrical engineering and computer science training with decades of practical genomics innovation.
19 years of coding experience
21 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of MarylandMS, Computer Engineering, MS, Computer Engineering at Stanford University
Github Skills (12)
algorithm10
c1710
bioinformatics10
data-structures10
algorithms10
c1110
data-structure10
genome-assembly10
statistic9
statistics9
architecture8
architectures8
Programming languages (2)
Github contributions (4)
marbl/canu
Mar 2007 - May 2007
A single molecule sequence assembler for genomes large and small.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:10 commits in 2 months
Contributions summary:Granger primarily contributed to the core logic of the `canu` assembler, focusing on improvements to the chi-squared test and the bottom-up clustering algorithm. Their work involved refactoring and optimizing code in C, specifically within the `MergeEdges_CGW.c` and `DemoteUnitigsWithRBP_CGW.c` files. The user also introduced a parameter to control unitig demotion, enhancing the configurability of the assembly process. These changes aimed to improve the accuracy and efficiency of genome assembly.
sequencegenomespipelinesingle-moleculeassembler
JCVenterInstitute/PanGenomePipeline
Sep 2018 - Sep 2022
PanGenomePipeline
Contributions:566 commits, 545 PRs, 268 pushes in 4 years
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