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분석 방법 변화에 따른 음성 대조군과 호흡기 검체 간 미생물 구성 차이 비교

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dc.contributor.authorKim, Hyojung-
dc.contributor.authorLee, Sang Pyo-
dc.contributor.authorKang, Shin Myung-
dc.contributor.authorKang, Sung-Yoon-
dc.contributor.authorJung, Sungwon-
dc.contributor.authorLee, Sang Min-
dc.date.available2020-02-27T09:41:55Z-
dc.date.created2020-02-06-
dc.date.issued2018-09-
dc.identifier.issn2288-0402-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/3394-
dc.description.abstractPurpose: Identifying microbial communities with 16S ribosomal RNA (rRNA) gene sequencing is a popular approach in microbiome studies, and various software tools and data resources have been developed for microbial analysis. Our aim in this study is investigating various available software tools and reference sequence databases to compare their performance in differentiating subject samples and negative controls. Methods: We collected 4 negative control samples using various acquisition protocols, and 2 respiratory samples were acquired from a healthy subject also with different acquisition protocols. Quantitative methods were used to compare the results of taxonomy compositions of these 6 samples by varying the configuration of analysis software tools and reference databases. Results: The results of taxonomy assignments showed relatively little difference, regardless of pipeline configurations and reference databases. Nevertheless, the effect on the discrepancy was larger using different software configurations than using different reference databases. In recognizing different samples, the 4 negative controls were clearly separable from the 2 subject samples. Additionally, there is a tendency to differentiate samples from different acquisition protocols. Conclusion: Our results suggest little difference in microbial compositions between different software tools and reference databases, but certain configurations can improve the separability of samples. Changing software tools shows a greater impact on results than changing reference databases; thus, it is necessary to utilize appropriate configurations based on the objectives of studies.-
dc.language한국어-
dc.language.isoko-
dc.publisherKOREAN ACAD ASTHMA ALLERGY & CLINICAL IMMUNOLOGY-
dc.relation.isPartOfALLERGY ASTHMA & RESPIRATORY DISEASE-
dc.title분석 방법 변화에 따른 음성 대조군과 호흡기 검체 간 미생물 구성 차이 비교-
dc.title.alternativeComparison of differences in microbial compositions between negative controls and subject samples with varying analysis configurations-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass2-
dc.identifier.wosid000446543100005-
dc.identifier.doi10.4168/aard.2018.6.5.255-
dc.identifier.bibliographicCitationALLERGY ASTHMA & RESPIRATORY DISEASE, v.6, no.5, pp.255 - 262-
dc.identifier.kciidART002385165-
dc.description.isOpenAccessN-
dc.citation.endPage262-
dc.citation.startPage255-
dc.citation.titleALLERGY ASTHMA & RESPIRATORY DISEASE-
dc.citation.volume6-
dc.citation.number5-
dc.contributor.affiliatedAuthorKim, Hyojung-
dc.contributor.affiliatedAuthorLee, Sang Pyo-
dc.contributor.affiliatedAuthorKang, Shin Myung-
dc.contributor.affiliatedAuthorKang, Sung-Yoon-
dc.contributor.affiliatedAuthorJung, Sungwon-
dc.contributor.affiliatedAuthorLee, Sang Min-
dc.type.docTypeArticle-
dc.subject.keywordAuthorMicrobiota-
dc.subject.keywordAuthorMetagenome-
dc.subject.keywordAuthorComputational biology-
dc.subject.keywordPlusRNA GENE DATABASE-
dc.subject.keywordPlusPROJECT-
dc.subject.keywordPlusGENOME-
dc.subject.keywordPlusIMPACT-
dc.relation.journalResearchAreaAllergy-
dc.relation.journalWebOfScienceCategoryAllergy-
dc.description.journalRegisteredClasskci-
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의과대학 > 의예과 > 1. Journal Articles
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