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- Title
SUGAR: graphical user interface-based data refiner for high-throughput DNA sequencing.
- Authors
Yukuto Sato; Kaname Kojima; Naoki Nariai; Yumi Yamaguchi-Kabata; Yosuke Kawai; Mamoru Takahashi; Takahiro Mimori; Masao Nagasaki
- Abstract
Background: Next-generation sequencers (NGSs) have become one of the main tools for current biology. To obtain useful insights from the NGS data, it is essential to control low-quality portions of the data affected by technical errors such as air bubbles in sequencing fluidics. Results: We develop a software SUGAR (subtile-based GUI-assisted refiner) which can handle ultra-high-throughput data with user-friendly graphical user interface (GUI) and interactive analysis capability. The SUGAR generates high-resolution quality heatmaps of the flowcell, enabling users to find possible signals of technical errors during the sequencing. The sequencing data generated from the error-affected regions of a flowcell can be selectively removed by automated analysis or GUI-assisted operations implemented in the SUGAR. The automated data-cleaning function based on sequence read quality (Phred) scores was applied to a public whole human genome sequencing data and we proved the overall mapping quality was improved. Conclusion: The detailed data evaluation and cleaning enabled by SUGAR would reduce technical problems in sequence read mapping, improving subsequent variant analysis that require high-quality sequence data and mapping results. Therefore, the software will be especially useful to control the quality of variant calls to the low population cells, e.g., cancers, in a sample with technical errors of sequencing procedures.
- Publication
BMC Genomics, 2014, Vol 15, Issue 1, p664
- ISSN
1471-2164
- Publication type
Article
- DOI
10.1186/1471-2164-15-664