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BMC Bioinformatics. 2016 Dec 1;17(1):490.

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

Author information

1
Department of Computer Science, University of California, Berkeley, 387 Soda Hall, Berkeley, 94720, USA.
2
Department of Computer Science, University of Michigan, 486 Vassar Avenue, Berkeley, CA, 94708, USA.
3
Innovative Genomics Initiative, University of California, Berkeley, 188 Li Ka Shing Center, Berkeley, CA, 94720, USA.
4
Faculty of Industrial Engineering, Mechanical Engineering and Computer Science, University of Iceland, Dunhagi 5, 107, Reykjavík, Iceland.
5
Department of Computer Science, University of California, Berkeley, 387 Soda Hall, Berkeley, 94720, USA. lpachter@math.berkeley.edu.
6
Departments of Mathematics and Molecular & Cell Biology, University of California at Berkeley, Berkeley, CA, 94720-3840, USA. lpachter@math.berkeley.edu.

Abstract

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 .

KEYWORDS:

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

PMID:
27905880
PMCID:
PMC5131447
DOI:
10.1186/s12859-016-1357-2
[Indexed for MEDLINE]
Free PMC Article

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