Journal Article

Methods developed during the first National Center for Biotechnology Information Structural Variation Codeathon at Baylor College of Medicine version 1; peer review: 1 approved, 1 approved with reservations

Jochum, Michael, Mitra, Shakuntala, Gener, Alejandro Rafael, Edrisi, Mohammadamin, Zheng, Rong, Sedlazeck, Fritz J, Wang, Junzhou, Foertter, Fernanda, Khayat, Michael M, English, Adam C, Lin, Chiao-Feng, Bae, Gigon, Hehn, Andreas, Busby, Ben, Kalra, Divya, Phan, Lon, Shah, Nirav N, Menon, Vipin K, Treangen, Todd J, Mahaganapathy, Vaidhyanathan, Liao, Chunxiao, Symer, David E, Kalla, Sara E, Du, Haowei, Akagi, Keiko, Feng, Yuanqing, Aliyev, Elbay, Venner, Eric, Balaji, Advait, Carvalho, Claudia M. B, Chin, Chen-Shan, Lo, Chun-Hsuan, Hefferon, Tim, Fungtammasan, Arkarachai, Fullem, Robert, Albin, Dreycey, Mahmoud, Medhat, Zhou, Anbo, Daw, Joyjit, Dawson, Eric T, Wang, Qi, Fu, Yilei, Diesh, Colin, Malladi, Venkat Sai, Chrisman, Brianna Sierra, Yin, Yongze

2020

Overview

In October 2019, 46 scientists from around the world participated in the first National Center for Biotechnology Information (NCBI) Structural Variation (SV) Codeathon at Baylor College of Medicine. The charge of this first annual working session was to identify ongoing challenges around the topics of SV and graph genomes, and in response to design reliable methods to facilitate their study. Over three days, seven working groups each designed and developed new open-sourced methods to improve the bioinformatic analysis of genomic SVs represented in next-generation sequencing (NGS) data. The groups' approaches addressed a wide range of problems in SV detection and analysis, including quality control (QC) assessments of metagenome assemblies and population-scale VCF files, de novo copy number variation (CNV) detection based on continuous long sequence reads, the representation of sequence variation using graph genomes, and the development of an SV annotation pipeline. A summary of the questions and developments that arose during the daily discussions between groups is outlined. The new methods are publicly available at https://github.com/NCBI-Codeathons/, and demonstrate that a codeathon devoted to SV analysis can produce valuable new insights both for participants and for the broader research community.

• Publisher: F1000 Research Ltd