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SUGAR: graphical user interface-based data refiner for high-throughput DNA sequencing

Yukuto Sato, Kaname Kojima, Naoki Nariai, Yumi Yamaguchi-Kabata, Yosuke Kawai, Mamoru Takahashi, Takahiro Mimori and Masao Nagasaki*

Author Affiliations

Department of Integrative Genomics, Tohoku Medial Megabank Organization, Tohoku University, 2–1 Seiryo-machi, Aoba-ku Sendai, Miyagi, 980-8573, Japan

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BMC Genomics 2014, 15:664  doi:10.1186/1471-2164-15-664

Published: 8 August 2014



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.


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.


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.

Automated analysis; Data cleaning; Illumina HiSeq; MiSeq; NGS