Comparison of the MGISEQ-2000 and Illumina HiSeq 4000 sequencing platforms for RNA sequencing

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dc.contributor.authorSol A Jeon-
dc.contributor.authorJong Lyul Park-
dc.contributor.authorJong Hwan Kim-
dc.contributor.authorJeong Hwan Kim-
dc.contributor.authorYong Sung Kim-
dc.contributor.authorJ C Kim-
dc.contributor.authorSeon-Young Kim-
dc.date.accessioned2020-02-07T16:30:06Z-
dc.date.available2020-02-07T16:30:06Z-
dc.date.issued2019-
dc.identifier.issnI000-0158-
dc.identifier.uri10.5808/GI.2019.17.3.e32ko
dc.identifier.urihttps://oak.kribb.re.kr/handle/201005/19047-
dc.description.abstractCurrently, Illumina sequencers are the globally leading sequencing platform in the next-generation sequencing market. Recently, MGI Tech launched a series of new sequencers, including the MGISEQ-2000, which promise to deliver high-quality sequencing data faster and at lower prices than Illumina's sequencers. In this study, we compared the performance of two major sequencers (MGISEQ-2000 and HiSeq 4000) to test whether the MGISEQ-2000 sequencer delivers high-quality sequence data as suggested. We performed RNA sequencing of four human colon cancer samples with the two platforms, and compared the sequencing quality and expression values. The data produced from the MGISEQ-2000 and HiSeq 4000 showed high concordance, with Pearson correlation coefficients ranging from 0.98 to 0.99. Various quality control (QC) analyses showed that the MGISEQ-2000 data fulfilled the required QC measures. Our study suggests that the performance of the MGISEQ-2000 is comparable to that of the HiSeq 4000 and that the MGISEQ-2000 can be a useful platform for sequencing.-
dc.publisherKorea Soc-Assoc-Inst-
dc.titleComparison of the MGISEQ-2000 and Illumina HiSeq 4000 sequencing platforms for RNA sequencing-
dc.title.alternativeComparison of the MGISEQ-2000 and Illumina HiSeq 4000 sequencing platforms for RNA sequencing-
dc.typeArticle-
dc.citation.titleGenomics & Informatics-
dc.citation.number3-
dc.citation.endPagee32-
dc.citation.startPagee32-
dc.citation.volume17-
dc.contributor.affiliatedAuthorSol A Jeon-
dc.contributor.affiliatedAuthorJong Lyul Park-
dc.contributor.affiliatedAuthorJong Hwan Kim-
dc.contributor.affiliatedAuthorJeong Hwan Kim-
dc.contributor.affiliatedAuthorYong Sung Kim-
dc.contributor.affiliatedAuthorSeon-Young Kim-
dc.contributor.alternativeName전솔아-
dc.contributor.alternativeName박종열-
dc.contributor.alternativeName김종환-
dc.contributor.alternativeName김정환-
dc.contributor.alternativeName김용성-
dc.contributor.alternativeName김진천-
dc.contributor.alternativeName김선영-
dc.identifier.bibliographicCitationGenomics & Informatics, vol. 17, no. 3, pp. e32-e32-
dc.identifier.doi10.5808/GI.2019.17.3.e32-
dc.subject.keywordHiSeq 4000-
dc.subject.keywordMGISEQ-2000-
dc.subject.keywordbenchmarking-
dc.subject.localHiSeq 4000-
dc.subject.localMGISEQ-2000-
dc.subject.localbenchmarking-
dc.subject.localBenchmarking-
dc.description.journalClassN-
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