Linfang Jin1, Jinhuo Lai2, Yang Zhang1, Ying Fu1, Shuhang Wang3, Heng Dai1, Bingding Huang1. 1. Department of Research and Development, Sinotech Genomics Inc., Shanghai, China. 2. Department of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, China. 3. Thoracic Medical Oncology Department, Peking University Cancer Hospital, Beijing, China.
Abstract
SUMMARY: Here we developed a tool called Breakpoint Identification (BreakID) to identity fusion events from targeted sequencing data. Taking discordant read pairs and split reads as supporting evidences, BreakID can identify gene fusion breakpoints at single nucleotide resolution. After validation with confirmed fusion events in cancer cell lines, we have proved that BreakID can achieve high sensitivity of 90.63% along with PPV of 100% at sequencing depth of 500× and perform better than other available fusion detection tools. We anticipate that BreakID will have an extensive popularity in the detection and analysis of fusions involved in clinical and research sequencing scenarios. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://github.com/SinOncology/BreakID. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
SUMMARY: Here we developed a tool called Breakpoint Identification (BreakID) to identity fusion events from targeted sequencing data. Taking discordant read pairs and split reads as supporting evidences, BreakID can identify gene fusion breakpoints at single nucleotide resolution. After validation with confirmed fusion events in cancer cell lines, we have proved that BreakID can achieve high sensitivity of 90.63% along with PPV of 100% at sequencing depth of 500× and perform better than other available fusion detection tools. We anticipate that BreakID will have an extensive popularity in the detection and analysis of fusions involved in clinical and research sequencing scenarios. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at https://github.com/SinOncology/BreakID. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.