NGSQC: Cross-platform quality analysis pipeline for deep sequencing data

Manhong Dai, Robert C. Thompson, Christopher Maher, Rafael Contreras-Galindo, Mark H. Kaplan, David M. Markovitz, Gil Omenn, Fan Meng

Research output: Contribution to journalArticlepeer-review

68 Scopus citations

Abstract

Background: 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.Results: The NGSQC (Next Generation Sequencing Quality Control) pipeline provides a set of novel quality control measures for quickly detecting a wide variety of quality issues in deep sequencing data derived from two dimensional surfaces, regardless of the assay technology used. It also enables researchers to determine whether sequencing data related to their most interesting biological discoveries are caused by sequencing quality issues.Conclusions: 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.

Original languageEnglish (US)
Article numberS7
JournalBMC Genomics
Volume11
Issue numberSUPPL. 4
DOIs
StatePublished - Dec 2 2010

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