MultiRankSeq : Multiperspective Approach for RNAseq Differential Expression Analysis and Quality Control
Joint Authors
Shyr, Yu
Sheng, Quanhu
Guo, Yan
Zhao, Shilin
Ye, Fei
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-05-27
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Background.
After a decade of microarray technology dominating the field of high-throughput gene expression profiling, the introduction of RNAseq has revolutionized gene expression research.
While RNAseq provides more abundant information than microarray, its analysis has proved considerably more complicated.
To date, no consensus has been reached on the best approach for RNAseq-based differential expression analysis.
Not surprisingly, different studies have drawn different conclusions as to the best approach to identify differentially expressed genes based upon their own criteria and scenarios considered.
Furthermore, the lack of effective quality control may lead to misleading results interpretation and erroneous conclusions.
To solve these aforementioned problems, we propose a simple yet safe and practical rank-sum approach for RNAseq-based differential gene expression analysis named MultiRankSeq.
MultiRankSeq first performs quality control assessment.
For data meeting the quality control criteria, MultiRankSeq compares the study groups using several of the most commonly applied analytical methods and combines their results to generate a new rank-sum interpretation.
MultiRankSeq provides a unique analysis approach to RNAseq differential expression analysis.
MultiRankSeq is written in R, and it is easily applicable.
Detailed graphical and tabular analysis reports can be generated with a single command line.
American Psychological Association (APA)
Guo, Yan& Zhao, Shilin& Ye, Fei& Sheng, Quanhu& Shyr, Yu. 2014. MultiRankSeq : Multiperspective Approach for RNAseq Differential Expression Analysis and Quality Control. BioMed Research International،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-457159
Modern Language Association (MLA)
Guo, Yan…[et al.]. MultiRankSeq : Multiperspective Approach for RNAseq Differential Expression Analysis and Quality Control. BioMed Research International No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-457159
American Medical Association (AMA)
Guo, Yan& Zhao, Shilin& Ye, Fei& Sheng, Quanhu& Shyr, Yu. MultiRankSeq : Multiperspective Approach for RNAseq Differential Expression Analysis and Quality Control. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-457159
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-457159