A graphical user interface for RAId, a knowledge integrated proteomics analysis suite with accurate statistics

BMC Research Notes. 2018;11(1):1-7 DOI 10.1186/s13104-018-3289-6

 

Journal Homepage

Journal Title: BMC Research Notes

ISSN: 1756-0500 (Online)

Publisher: BMC

LCC Subject Category: Medicine | Science: Biology (General)

Country of publisher: United Kingdom

Language of fulltext: English

Full-text formats available: PDF, HTML

 

AUTHORS

Brendan Joyce (National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health)
Danny Lee (National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health)
Alex Rubio (National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health)
Aleksey Ogurtsov (National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health)
Gelio Alves (National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health)
Yi-Kuo Yu (National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health)

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 15 weeks

 

Abstract | Full Text

Abstract Objective RAId is a software package that has been actively developed for the past 10 years for computationally and visually analyzing MS/MS data. Founded on rigorous statistical methods, RAId’s core program computes accurate E-values for peptides and proteins identified during database searches. Making this robust tool readily accessible for the proteomics community by developing a graphical user interface (GUI) is our main goal here. Results We have constructed a graphical user interface to facilitate the use of RAId on users’ local machines. Written in Java, RAId_GUI not only makes easy executions of RAId but also provides tools for data/spectra visualization, MS-product analysis, molecular isotopic distribution analysis, and graphing the retrieval versus the proportion of false discoveries. The results viewer displays and allows the users to download the analyses results. Both the knowledge-integrated organismal databases and the code package (containing source code, the graphical user interface, and a user manual) are available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads/raid.html.