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

dc.contributor.authorDai, Manhong
dc.contributor.authorThompson, Robert C
dc.contributor.authorMaher, Christopher
dc.contributor.authorContreras-Galindo, Rafael
dc.contributor.authorKaplan, Mark H
dc.contributor.authorMarkovitz, David M
dc.contributor.authorOmenn, Gil
dc.contributor.authorMeng, Fan
dc.date.accessioned2015-08-07T17:44:14Z
dc.date.available2015-08-07T17:44:14Z
dc.date.issued2010-12-02
dc.identifier.citationBMC Genomics. 2010 Dec 02;11(Suppl 4):S7
dc.identifier.urihttps://hdl.handle.net/2027.42/112794en_US
dc.description.abstractAbstract 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.
dc.titleNGSQC: cross-platform quality analysis pipeline for deep sequencing data
dc.typeArticleen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/112794/1/12864_2010_Article_3466.pdf
dc.identifier.doi10.1186/1471-2164-11-S4-S7en_US
dc.language.rfc3066en
dc.rights.holderDai et al.
dc.date.updated2015-08-07T17:44:14Z
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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