Multi-perspective quality control of Illumina exome sequencing data using QC3

Yan Guo, Shilin Zhao, Quanhu Sheng, Fei Ye, Jiang Li, Brian Lehmann, Jennifer Pietenpol, David C. Samuels, Yu Shyr

Research output: Contribution to journalArticlepeer-review

60 Citations (Scopus)


Advances in next-generation sequencing (NGS) technologies have greatly improved our ability to detect genomic variants for biomedical research. The advance in NGS technologies has also created significant challenges in bioinformatics. One of the major challenges is the quality control of sequencing data. There has been heavy focus on performing raw data quality control. In order to correctly interpret the quality of the DNA sequencing data, however, proper quality control should be conducted at all stages of DNA sequencing data analysis: raw data, alignment, and variant detection. We designed QC3, a quality control tool aimed at those three major stages of DNA sequencing. QC3 monitors quality control metrics at each stage of NGS data and provides unique and independent evaluations of the data quality from different perspectives. QC3 offers unique features such as detection of batch effect and cross contamination. QC3 and its source code are freely downloadable at

Original languageEnglish
Pages (from-to)323-328
Number of pages6
Issue number5-6
Publication statusPublished - 2014

All Science Journal Classification (ASJC) codes

  • Genetics


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