Published in

Oxford University Press, Bioinformatics, 3(33), p. 447-449, 2016

DOI: 10.1093/bioinformatics/btw624

Links

Tools

Export citation

Search in Google Scholar

The START App: a web-based RNAseq analysis and visualization resource

Journal article published in 2016 by Jonathan W. Nelson, Jiri Sklenar, Anthony P. Barnes, Jessica Minnier ORCID
This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

Full text: Unavailable

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Abstract Summary Transcriptional profiling using RNA sequencing (RNAseq) has emerged as a powerful methodology to quantify global gene expression patterns in various contexts from single cells to whole tissues. The tremendous amount of data generated by this profiling technology presents a daunting challenge in terms of effectively visualizing and interpreting results. Convenient and intuitive data interfaces are critical for researchers to easily upload, analyze and visualize their RNAseq data. We designed the START (Shiny Transcriptome Analysis Resource Tool) App with these requirements in mind. This application has the power and flexibility to be resident on a local computer or serve as a web-based environment, enabling easy sharing of data between researchers and collaborators. Availability and Implementation Source Code for the START App is written entirely in R and can be freely available to download at https://github.com/jminnier/STARTapp with the code licensed under GPLv3. It can be launched on any system that has R installed. The START App is also hosted on https://kcvi.shinyapps.io/START for researchers to temporarily upload their data.