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Kai Wang

Detecting DNA modifications and structural variants from nanopore long-read sequencing data

About Kai Wang

Dr. Kai Wang is an Associate Professor at the Raymond G. Perelman Center for Cellular and Molecular Therapeutics of the Children’s Hospital of Philadelphia, and Department of Pathology & Laboratory Medicine at the University of Pennsylvania’s Perelman School of Medicine. He received a Bachelor’s degree from Peking University in China, a master’s degree from the Mayo Clinic, and a PhD from the University of Washington. He had postdoctoral training at the University of Pennsylvania and the Children’s Hospital of Philadelphia, before becoming an Assistant Professor, and later Associate Professor at the University of Southern California Keck school of Medicine, and then Columbia University Medical Center. His research focuses on the development and application of genomic approaches to study the genetic basis of human diseases and facilitate the implementation of genomic medicine.

Recent publications

Liu, Q., Georgieva, D. C., Egli, D. & Wang, K. NanoMod: a computational tool to detect DNA modifications using nanopore long-read sequencing data. bioRxiv 277178 (2018). doi:10.1101/277178

Abstract

Compared to short-read sequencing techniques, Oxford Nanopore Technologies long-read sequencing platform has several advantages, such as the ability to detect DNA modifications directly from electric signals, and the improved sensitivity to find structural variants. Here we describe a novel method called NanoMod to improve the performance of detecting DNA modifications, especially synthetically introduced modifications, by analyzing the characteristics of raw signal intensities. We also describe a data handling pipeline for detecting structural variants from long-read data. We illustrate a few examples of pinpointing the exact breakpoints of balanced translocations or identifying causal structural variants in exome-negative patients, which subsequently enabled pre-implementation genetic diagnosis.

Kai Wang

Kai Wang

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