Billy Rowell is a Senior Bioinformatics Scientist on the Bioinformatics Applications Team at PacBio. His research interests include the detection and phasing of small variants in long read sequencing data. He has experience in classical genetics in model organisms, neurogenetics, and human genetics. At PacBio, he has focused on the detection and phasing of variants in targeted capture or whole genome sequencing data from human samples.
MA in Molecular and Cell Biology, 2010
University of California, Berkeley
BS Biology with Chemistry minor, 2002
University of North Carolina, Chapel Hill
shell scripting, HPC clusters & version control • Python, Jupyter, NumPy, pandas & Matplotlib • reproducible analysis • next generation sequencing and third generation sequencing applications, including whole genome sequencing, targeted sequencing, RNASeq, and Iso-Seq • interpreting the quality of sequencing data • bioinformatic tools including BWA, Bowtie, STAR, GATK, minimap2, samtools, bedtools, bcftools, whatshap • designing and maintaining production grade bioinformatics analysis workflows • 20 years of experience administering home Linux servers and workstations
quality control, critical interpretation & troubleshooting problems with NGS data • nucleic acid isolation, manipulation, cloning & analysis • RNA in situ hybridization & visualization • bacterial genetics, fruit fly husbandry & classical eukaryotic genetics
adapting techniques, off-the-shelf products & custom hardware and software • experimental design & protocol refinement • equipment testing, calibration & maintenance • logistics for high-throughput operation • wide field microscopy & confocal fluorescence microscopy • image acquisition & analysis
proven track record in collaborative science • determined problem solver & data-driven process improvement • training researchers in biological techniques & laboratory management skills • training researchers in introductory programming & best practices • liaising and translating between research staff & operations staff • consulting for sales, project managers & clients • presenting data in written & oral formats
Research Specialist (2013-2015)
Research Technician (2010-2013)
Department: Project Technical Resources (Sep 2012 - Sep 2015)
Description: I supported the research of the project teams and labs at Janelia by providing consultation, conducting experiments, analyzing data, and writing software.
Accomplishments: acted as liaison and translator between different disciplines • screened over 200 Drosophila melanogaster lines through high-throughput locomotor / optomotor / phototaxis assay • screened over 300 D. mel. lines through high-throughput olfactory assay • curated and analyzed data and metadata • aided in design of novel behavioral assays, including instrument design and testing, protocol refinement, and data analysis tools • wrote suite of tools for analysis of D. mel. activity / sleep data • wrote and maintained automated pipeline for fluorescence imagery analysis
Department: Fly Olympiad Team Project (Mar 2010 - Sep 2012)
Description: I investigated the role of individual neurons or groups of neurons in altering behavior by screening Drosophila melanogaster lines through high-throughput behavioral assays.
Accomplishments: acted as liaison and translator between different disciplines in large-scale scientific collaboration • screened over 2000 D. mel. lines through high-throughput locomotor / optomotor / phototaxis assay • aided in establishing guidelines for storing data and metadata • aided in establishing a more flexible scheme for describing line nomenclature and relationships
A public-private-academic consortium hosted by NIST to develop reference materials and standards for clinical sequencing
The DNA sequencing technologies in use today produce either highly accurate short reads or less-accurate long reads. We report the optimization of circular consensus sequencing (CCS) to improve the accuracy of single-molecule real-time (SMRT) sequencing (PacBio) and generate highly accurate (99.8%) long high-fidelity (HiFi) reads with an average length of 13.5 kilobases (kb). We applied our approach to sequence the well-characterized human HG002/NA24385 genome and obtained precision and recall rates of at least 99.91% for single-nucleotide variants (SNVs), 95.98% for insertions and deletions <50 bp (indels) and 95.99% for structural variants. Our CCS method matches or exceeds the ability of short-read sequencing to detect small variants and structural variants. We estimate that 2,434 discordances are correctable mistakes in the ‘genome in a bottle’ (GIAB) benchmark set. Nearly all (99.64%) variants can be phased into haplotypes, further improving variant detection. De novo genome assembly using CCS reads alone produced a contiguous and accurate genome with a contig N50 of >15 megabases (Mb) and concordance of 99.997%, substantially outperforming assembly with less-accurate long reads.