Polyester: simulating RNA-seq datasets with differential transcript expression | Zendy

Alyssa C. Frazee | Zendy; Andrew E. Jaffe | Zendy; Ben Langmead | Zendy; Jeffrey T. Leek | Zendy

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Polyester: simulating RNA-seq datasets with differential transcript expression

Author(s) -

Alyssa C. Frazee,

Andrew E. Jaffe,

Ben Langmead,

Jeffrey T. Leek

Publication year - 2015

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btv272

Subject(s) - bioconductor , computer science , expression (computer science) , differential (mechanical device) , rna seq , workflow , software , data mining , rna , set (abstract data type) , computational biology , biology , gene expression , database , transcriptome , genetics , gene , programming language , engineering , aerospace engineering

Statistical methods development for differential expression analysis of RNA sequencing (RNA-seq) requires software tools to assess accuracy and error rate control. Since true differential expression status is often unknown in experimental datasets, artificially constructed datasets must be utilized, either by generating costly spike-in experiments or by simulating RNA-seq data.

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