DocumentCode :
3453409
Title :
The effect of human genome annotation complexity on RNA-Seq gene expression quantification
Author :
Po-Yen Wu ; Phan, John H. ; Wang, May Dongmei
Author_Institution :
Dept. of Electr. & Comput. Eng., Georgia Tech, Atlanta, GA, USA
fYear :
2012
fDate :
4-7 Oct. 2012
Firstpage :
712
Lastpage :
717
Abstract :
Next-generation sequencing (NGS) has brought human genomie research to an unprecedented era. RNA-Seq is a branch of NGS that can be used to quantify gene expression and depends on accurate annotation of the human genome (i.e., the definition of genes and all of their variants or isoforms). Multiple annotations of the human genome exist with varying complexity. However, it is not clear how the choice of genome annotation influences RNA-Seq gene expression quantification. We assess the effect of different genome annotations in terms of (1) mapping quality, (2) quantification variation, (3) quantification accuracy (i.e., by comparing to qRT-PCR data), and (4) the concordance of detecting differentially expressed genes. External validation with qRT-PCR suggests that more complex genome annotations result in higher quantification variation.
Keywords :
RNA; biology computing; genomics; NGS; RNA-Seq gene expression quantification; differentially expressed gene detection; human genome; human genome annotation complexity; mapping quality; next-generation sequencing; qRT-PCR data; quantification accuracy; quantification variation; Bioinformatics; Complexity theory; Databases; Gene expression; Genomics; Humans; RNA; RNA-Seq; annotation complexity; differential expression; human genome annotation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine Workshops (BIBMW), 2012 IEEE International Conference on
Conference_Location :
Philadelphia, PA
Print_ISBN :
978-1-4673-2746-6
Electronic_ISBN :
978-1-4673-2744-2
Type :
conf
DOI :
10.1109/BIBMW.2012.6470224
Filename :
6470224
Link To Document :
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