Title |
Assessing the impact of human genome annotation choice on RNA-seq expression estimates
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Published in |
BMC Bioinformatics, November 2013
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DOI | 10.1186/1471-2105-14-s11-s8 |
Pubmed ID | |
Authors |
Po-Yen Wu, John H Phan, May D Wang |
Abstract |
Genome annotation is a crucial component of RNA-seq data analysis. Much effort has been devoted to producing an accurate and rational annotation of the human genome. An annotated genome provides a comprehensive catalogue of genomic functional elements. Currently, at least six human genome annotations are publicly available, including AceView Genes, Ensembl Genes, H-InvDB Genes, RefSeq Genes, UCSC Known Genes, and Vega Genes. Characteristics of these annotations differ because of variations in annotation strategies and information sources. When performing RNA-seq data analysis, researchers need to choose a genome annotation. However, the effect of genome annotation choice on downstream RNA-seq expression estimates is still unclear. This study (1) investigates the effect of different genome annotations on RNA-seq quantification and (2) provides guidelines for choosing a genome annotation based on research focus. |
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Mendeley readers
Geographical breakdown
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Japan | 2 | 2% |
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Czechia | 1 | <1% |
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Student > Bachelor | 6 | 5% |
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Unknown | 11 | 9% |
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Engineering | 4 | 3% |
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