Sneha D. Goenka is a PhD candidate in the Department of Electrical Engineering at Stanford University where she is advised by Prof. Mark Horowitz. Her current research interests lie at the intersection of computer architecture and computational genomics. She has a B.Tech and M.Tech (Microelectronics) in Electrical Engineering from Indian Institute of Technology, Bombay.
Accelerated identification of disease-causing variants with ultra-rapid nanopore genome sequencing.
Whole-genome sequencing (WGS) can identify variants that cause genetic disease, but the time required for sequencing and analysis has been a barrier to its use in acutely ill patients. In the present study, we develop an approach for ultra-rapid nanopore WGS that combines an optimized sample preparation protocol, distributing sequencing over 48 flow cells, near real-time base calling and alignment, accelerated variant calling and fast variant filtration for efficient manual review. Application to two example clinical cases identified a candidate variant in <8 h from sample preparation to variant identification. We show that this framework provides accurate variant calls and efficient prioritization, and accelerates diagnostic clinical genome sequencing twofold compared with previous approaches.
View details for DOI 10.1038/s41587-022-01221-5
View details for PubMedID 35347328
Ultra-Rapid Nanopore Whole Genome Genetic Diagnosis of Dilated Cardiomyopathy in an Adolescent With Cardiogenic Shock.
Circulation. Genomic and precision medicine
View details for DOI 10.1161/CIRCGEN.121.003591
View details for PubMedID 35133172
Ultrarapid Nanopore Genome Sequencing in a Critical Care Setting.
The New England journal of medicine
View details for DOI 10.1056/NEJMc2112090
View details for PubMedID 35020984
SegAlign: A Scalable GPU-Based Whole Genome Aligner
International Conference for High Performance Computing, Networking, Storage and Analysis (SC)
View details for DOI 10.1109/SC41405.2020.00043
Darwin-WGA: A Co-processor Provides Increased Sensitivity in Whole Genome Alignments with High Speedup
IEEE. 2019: 359–72
View details for DOI 10.1109/HPCA.2019.00050
View details for Web of Science ID 000469766300028