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G. Zhang
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P2.02 - Biology/Pathology (ID 616)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Biology/Pathology
- Presentations: 1
- Moderators:
- Coordinates: 10/17/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P2.02-006 - NovoSV: Identify and Parse the Pattern of Chromosomal Structural Variation (ID 8283)
09:30 - 09:30 | Author(s): G. Zhang
- Abstract
Background:
With the development of High-throughput DNA sequencing technologies, several tools have been developed aim at searching structural variations. However, most of available structural variation predication tools can only identity the abnormal connections, a systematically parsing the pattern of structure variation to obtain the length and connection type of SVs is still tough work.
Method:
In this study, we present a tool, NovoSV, which can identify the abnormal connections precisely, and based on associated abnormal connections NovoSV will report the length and connection type of the structural variation.
Result:
NovoSV took a BWA mapped results as input and identified abnormal connections and pattern of chromosomal structure variations would be reported. For validation, NovoSV was applied to target sequencing data derived from 10 samples, NovoSV identified 8 abnormal connections, and 7 of these results could be validated by polymerase chain reaction (PCR). When applied to whole-genome sequencing data derived from 5 samples, NovoSV reported 46 SVs with their length and connection type. Of the 4 random selected identified results, 3 were validated by Sanger sequencing.
Conclusion:
NovoSV is an efficient tool for chromosomal variation detection, which can accurately identify abnormal connections and parse the pattern of chromosomal variations. NovoSV has been validated on GNU/Linux systems, and an open source PERL program is available.
