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Overview of available methods for diverse RNA-Seq data analyses.
MedLine Citation:
PMID:  22227904     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
RNA-Seq technology is becoming widely used in various transcriptomics studies; however, analyzing and interpreting the RNA-Seq data face serious challenges. With the development of high-throughput sequencing technologies, the sequencing cost is dropping dramatically with the sequencing output increasing sharply. However, the sequencing reads are still short in length and contain various sequencing errors. Moreover, the intricate transcriptome is always more complicated than we expect. These challenges proffer the urgent need of efficient bioinformatics algorithms to effectively handle the large amount of transcriptome sequencing data and carry out diverse related studies. This review summarizes a number of frequently-used applications of transcriptome sequencing and their related analyzing strategies, including short read mapping, exon-exon splice junction detection, gene or isoform expression quantification, differential expression analysis and transcriptome reconstruction.
Authors:
Geng Chen; Charles Wang; Tieliu Shi
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Publication Detail:
Type:  Journal Article     Date:  2012-01-07
Journal Detail:
Title:  Science China. Life sciences     Volume:  54     ISSN:  1869-1889     ISO Abbreviation:  Sci China Life Sci     Publication Date:  2011 Dec 
Date Detail:
Created Date:  2012-01-09     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101529880     Medline TA:  Sci China Life Sci     Country:  China    
Other Details:
Languages:  eng     Pagination:  1121-8     Citation Subset:  IM    
Affiliation:
Center for Bioinformatics and Computational Biology, Institute of Biomedical Sciences, School of Life Science, East China Normal University, Shanghai, 200241, China.
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