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Computational methods for transcriptome annotation and quantification using RNA-seq

delete2011-05-27
delete957
PRE
AI
M
Manuel Garber *
M
Manfred Grabherr
M
Mitchell Guttman
C
Cole Trapnell
DOI:10.1038/NMETH.1613delete
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摘要

摘要

En 中文
High-throughput RNA sequencing (RNA-seq) promises a comprehensive picture of the transcriptome, allowing for the complete annotation and quantification of all genes and their isoforms across samples. Realizing this promise requires increasingly complex computational methods. These computational challenges fall into three main categories: (i) read mapping, (ii) transcriptome reconstruction and (iii) expression quantification. Here we explain the major conceptual and practical challenges, and the general classes of solutions for each category. Finally, we highlight the interdependence between these categories and discuss the benefits for different biological applications.
Keyword:
DIFFERENTIAL EXPRESSION ANALYSIS
MESSENGER-RNA
SPLICE JUNCTIONS
ALIGNMENT
GENOME
REVEALS
TOOL
NORMALIZATION
CONSTRUCTION
LANDSCAPE
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Nature Methods 封面图
Nature Methods
IF:
32.1
论文数:
7.3K
被引数:
12.7W

机构

H
Harvard University
学者数:
26.5W
论文数: 22.0W
被引数: 28.7W
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