Author:
Dai Manhong,Thompson Robert C,Maher Christopher,Contreras-Galindo Rafael,Kaplan Mark H,Markovitz David M,Omenn Gil,Meng Fan
Abstract
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 (N ext G eneration S equencing Q uality C ontrol) 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.
Publisher
Springer Science and Business Media LLC
Cited by
89 articles.
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