On Differential Gene expression Using RNA-Seq Data | Zendy

Ju Hee Lee | Zendy; Yuan Ji | Zendy; Shoudan Liang | Zendy; Guoshuai Cai | Zendy; Peter Müller | Zendy

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On Differential Gene expression Using RNA-Seq Data

Author(s) -

Ju Hee Lee,

Yuan Ji,

Shoudan Liang,

Guoshuai Cai,

Peter Müller

Publication year - 2011

Publication title -

cancer informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.606

H-Index - 31

ISSN - 1176-9351

DOI - 10.4137/cin.s7473

Subject(s) - rna seq , inference , computational biology , computer science , gene expression , gene , position (finance) , set (abstract data type) , rna , data set , bayesian probability , data mining , biology , genetics , artificial intelligence , transcriptome , finance , economics , programming language

RNA-Seq is a novel technology that provides read counts of RNA fragments in each gene, including the mapped positions of each read within each gene. Besides many other applications it can be used to detect differentially expressed genes. Most published methods collapse the position-level read data into a single gene-specific expression measurement. Statistical inference proceeds by modeling these gene-level expression measurements.

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