powsimR: power analysis for bulk and single cell RNA-seq experiments | Zendy

Beate Vieth | Zendy; Christoph Ziegenhain | Zendy; Swati Parekh | Zendy; Wolfgang Enard | Zendy; Ines Hellmann | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

powsimR: power analysis for bulk and single cell RNA-seq experiments

Author(s) -

Beate Vieth,

Christoph Ziegenhain,

Swati Parekh,

Wolfgang Enard,

Ines Hellmann

Publication year - 2017

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/btx435

Subject(s) - rna seq , computer science , power analysis , a priori and a posteriori , rna , power (physics) , r package , computational biology , data mining , software , gene , gene expression , biology , algorithm , genetics , transcriptome , computational science , programming language , philosophy , physics , epistemology , quantum mechanics , cryptography

Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes in RNA-seq data. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research