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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44265

Title: RNA-seq Coverage Effects on Biological Pathways and GO Tag Clouds
Authors: Chien-Ming Chen
Tsan-Huang Shih
Tun-Wen Pai
Zhen-Long Liu
Margaret Dah-Tsyr Chang
Contributors: 國立臺灣海洋大學:資訊工程學系
NTOU:Department of Computer Science and Engineering
Keywords: Gene Ontology
temporal pathway
RNA-seq
cross-strain comparison
Date: 2012-08
Issue Date: 2017-11-20T08:28:13Z
Publisher: 2012 IEEE International Conference on Systems Biology (ISB)
Abstract: Abstract:RNA-seq data analysis not only detects novel transcripts, promoters, and single nucleotide polymorphisms in a transcriptome scale, but also shows quantitative measurement of gene expression. In order to perform differential expression analysis for unraveling biological functions, we proposed a workflow which integrated annotations from KEGG biological pathways and Gene Ontology associations for manipulating multiple RNA-seq datasets. The developed system started from mapping short reads onto reference genes, and then performed normalization procedures on read coverage to evaluate and compare expression levels within various gene clusters. Different levels of gene expression were indicated by diverse color shades and graphically shown in designed temporal pathways. Besides, representative GO terms associated with differentially expressed gene cluster were also visually displayed by a GO tag cloud representation. Three different public RNA-seq datasets were applied to demonstrate that the proposed workflow could provide effective and efficient analysis on differential gene expression for either cross-strain comparison or an identical sample sequenced at different time points.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/44265
Appears in Collections:[資訊工程學系] 演講及研討會

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