PT  - JOURNAL ARTICLE
AU  - Oana Carja
AU  - Tongji Xing
AU  - Joshua B. Plotkin
AU  - Premal Shah
TI  - <strong>riboviz</strong>: analysis and visualization of ribosome profiling datasets
AID  - 10.1101/100032
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 100032
4099  - http://biorxiv.org/content/early/2017/01/12/100032.short
4100  - http://biorxiv.org/content/early/2017/01/12/100032.full
AB  - Using high-throughput sequencing to monitor translation in vivo, ribosome profiling can provide critical insights into the dynamics and regulation of protein synthesis in a cell. Since its introduction in 2009, this technique has played a key role in driving biological discovery, and yet it requires a rigorous computational toolkit for widespread adoption. We developed a processing pipeline and browser-based visualization, riboviz, that allows convenient exploration and analysis of riboseq datasets. In implementation, riboviz consists of a comprehensive and flexible backend analysis pipeline that allows the user to analyze their private unpublished dataset, along with a web application for comparison with previously published public datasets.Availability and implementation JavaScript and R source code and extra documentation are freely available from https://github.com/shahpr/RiboViz, while the web-application is live at www.riboviz.org.