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A Simple Guideline to Assess the Characteristics of RNA-Seq Data
Joint Authors
Han, Kyudong
Kang, Keunsoo
Son, Keunhong
Yu, Sungryul
Shin, Wonseok
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-11-04
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Son, Keunhong& Yu, Sungryul& Shin, Wonseok& Han, Kyudong& Kang, Keunsoo. 2018. A Simple Guideline to Assess the Characteristics of RNA-Seq Data. BioMed Research International،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1125487
Modern Language Association (MLA)
Son, Keunhong…[et al.]. A Simple Guideline to Assess the Characteristics of RNA-Seq Data. BioMed Research International No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1125487
American Medical Association (AMA)
Son, Keunhong& Yu, Sungryul& Shin, Wonseok& Han, Kyudong& Kang, Keunsoo. A Simple Guideline to Assess the Characteristics of RNA-Seq Data. BioMed Research International. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1125487
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1125487