VisRseq: R-based visual framework for analysis of sequencing data.
BACKGROUND
Several tools have been developed to enable biologists to perform initial browsing and exploration of sequencing data. However the computational tool set for further analyses often requires significant computational expertise to use and many of the biologists with the knowledge needed to interpret these data must rely on programming experts.


RESULTS
We present VisRseq, a framework for analysis of sequencing datasets that provides a computationally rich and accessible framework for integrative and interactive analyses without requiring programming expertise. We achieve this aim by providing R apps, which offer a semi-auto generated and unified graphical user interface for computational packages in R and repositories such as Bioconductor. To address the interactivity limitation inherent in R libraries, our framework includes several native apps that provide exploration and brushing operations as well as an integrated genome browser. The apps can be chained together to create more powerful analysis workflows.


CONCLUSIONS
To validate the usability of VisRseq for analysis of sequencing data, we present two case studies performed by our collaborators and report their workflow and insights.
Hamid
H
Younesy
Torsten
T
Möller
Matthew C
MC
Lorincz
Mohammad M
MM
Karimi
Steven J M
SJ
Jones
D000818:Animals; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D030561:Databases, Nucleic Acid; D053595:Embryonic Stem Cells / Q000378:metabolism*; D020869:Gene Expression Profiling; D005787:Gene Frequency; D016678:Genome; D005854:Germ Cells / Q000378:metabolism*; D059014:High-Throughput Nucleotide Sequencing; D020407:Internet; D051379:Mice; D008810:Mice, Inbred C57BL; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software; D014327:Trophoblasts; D014584:User-Computer Interface; D057188:Workflow