This article is part of the supplement: Ninth International Conference on Bioinformatics (InCoB2010): Computational Biology
NGSQC: cross-platform quality analysis pipeline for deep sequencing data
1 Department of Psychiatry and Molecular and Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, MI 48109, USA
2 Michigan Center for Translational Pathology, Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA
3 Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA
4 Center for Computational Medicine and Biology, University of Michigan, Ann Arbor, MI 48109, USA
5 National Center for Integrative Biomedical Informatics, University of Michigan, Ann Arbor, MI 48109, USA
Citation and License
BMC Genomics 2010, 11(Suppl 4):S7 doi:10.1186/1471-2164-11-S4-S7Published: 2 December 2010
While the accuracy and precision of deep sequencing data is significantly better than those obtained by the earlier generation of hybridization-based high throughput technologies, the digital nature of deep sequencing output often leads to unwarranted confidence in their reliability.
The NGSQC (
Next generation sequencing platforms have their own share of quality issues and there can be significant lab-to-lab, batch-to-batch and even within chip/slide variations. NGSQC can help to ensure that biological conclusions, in particular those based on relatively rare sequence alterations, are not caused by low quality sequencing.