A Simple Guideline to Assess the Characteristics of RNA-Seq Data.
Next-generation sequencing (NGS) techniques have been used to generate various molecular maps including genomes, epigenomes, and transcriptomes. Transcriptomes from a given cell population can be profiled via RNA-seq. However, there is no simple way to assess the characteristics of RNA-seq data syst...
| Publicado en: | BioMed Research International pp. 1 - 10 |
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| Autores principales: | , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
11/04/2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=132821927&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 132821927 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 11/04/2018 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 132821927 132821927 132821927 10.1155/2018/2906292 132821927 ppf: 1 ppct: 9 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A Simple Guideline to Assess the Characteristics of RNA-Seq Data. aug: au: Son, Keunhong Yu, Sungryul Shin, Wonseok Han, Kyudong Kang, Keunsoo affil: Department of Microbiology, College of Natural Sciences, Dankook University, Cheonan 31116, Republic of Korea sug: subj: RNA Sequence Analysis Methods Human Factor Analysis Gene Expression Carcinoma, Ductal ab: Next-generation sequencing (NGS) techniques have been used to generate various molecular maps including genomes, epigenomes, and transcriptomes. Transcriptomes from a given cell population can be profiled via RNA-seq. However, there is no simple way to assess the characteristics of RNA-seq data systematically. In this study, we provide a simple method that can intuitively evaluate RNA-seq data using two different principal component analysis (PCA) plots. The gene expression PCA plot provides insights into the association between samples, while the transcript integrity number (TIN) score plot provides a quality map of given RNA-seq data. With this approach, we found that RNA-seq datasets deposited in public repositories often contain a few low-quality RNA-seq data that can lead to misinterpretations. The effect of sampling errors for differentially expressed gene (DEG) analysis was evaluated with ten RNA-seq data from invasive ductal carcinoma tissues and three RNA-seq data from adjacent normal tissues taken from a Korean breast cancer patient. The evaluation demonstrated that sampling errors, which select samples that do not represent a given population, can lead to different interpretations when conducting the DEG analysis. Therefore, the proposed approach can be used to avoid sampling errors prior to RNA-seq data analysis. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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