APOSTL: An Interactive Galaxy Pipeline for Reproducible Analysis of Affinity Proteomics Data
详细信息 查看全文
- 作者：Brent M. Kuenzi ; Adam L. Borne ; Jiannong Li ; Eric B. Haura ; Steven A. Eschrich ; John M. Koomen ; Uwe Rix ; Paul A. Stewart
- 刊名：Journal of Proteome Research
- 出版年：2016
- 出版时间：December 2, 2016
- 年：2016
- 卷：15
- 期：12
- 页码：4747-4754
- 全文大小：549K
- ISSN：1535-3907
文摘
With continuously increasing scale and depth of coverage in affinity proteomics (AP–MS) data, the analysis and visualization is becoming more challenging. A number of tools have been developed to identify high-confidence interactions; however, a cohesive and intuitive pipeline for analysis and visualization is still needed. Here we present Automated Processing of SAINT Templated Layouts (APOSTL), a freely available Galaxy-integrated software suite and analysis pipeline for reproducible, interactive analysis of AP–MS data. APOSTL contains a number of tools woven together using Galaxy workflows, which are intuitive for the user to move from raw data to publication-quality figures within a single interface. APOSTL is an evolving software project with the potential to customize individual analyses with additional Galaxy tools and widgets using the R web application framework, Shiny. The source code, data, and documentation are freely available from GitHub (https://github.com/bornea/APOSTL) and other sources.