The Lair: a resource for exploratory analysis of published RNA-Seq data

BMC Bioinformatics

Database

Harold Pimentel¹  Lior Pachter²  Pascal Sturmfels³  Páll Melsted⁴  Nicolas Bray⁵ 

[1] Department of Computer Science, University of California, Berkeley, 387 Soda Hall, 94720, Berkeley, USA;Department of Computer Science, University of California, Berkeley, 387 Soda Hall, 94720, Berkeley, USA;Departments of Mathematics and Molecular & Cell Biology, University of California at Berkeley, 94720-3840, Berkeley, CA, USA;Department of Computer Science, University of Michigan, 486 Vassar Avenue, 94708, Berkeley, CA, USA;Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland, Dunhagi 5, 107, Reykjavík, Iceland;Innovative Genomics Initiative, University of California, Berkeley, 188 Li Ka Shing Center, 94720, Berkeley, CA, USA;

关键词: RNA-Seq;    Sequence read archive;    Exploratory data analysis;    Shiny;    Interactive visualization;    Reanalysis;    Reproducibility;    Kallisto;    Sleuth;   

DOI  :  10.1186/s12859-016-1357-2

 received in 2016-06-03, accepted in 2016-11-19,  发布年份 2016

来源: Springer

【 摘 要 】

Increased emphasis on reproducibility of published research in the last few years has led to the large-scale archiving of sequencing data. While this data can, in theory, be used to reproduce results in papers, it is difficult to use in practice. We introduce a series of tools for processing and analyzing RNA-Seq data in the Sequence Read Archive, that together have allowed us to build an easily extendable resource for analysis of data underlying published papers. Our system makes the exploration of data easily accessible and usable without technical expertise. Our database and associated tools can be accessed at The Lair: http://pachterlab.github.io/lair.

【 授权许可】

CC BY   
© The Author(s). 2016