SUBAcon: a consensus algorithm for unifying the subcellular localization data of the Arabidopsis proteome

• Published in: Bioinformatics Vol. 30; no. 23; pp. 3356 - 3364
• Main Authors: Hooper, Cornelia M., Tanz, Sandra K., Castleden, Ian R., Vacher, Michael A., Small, Ian D., Millar, A. Harvey
• Format: Journal Article
• Language: English
• Published: England 01.12.2014
• Subjects: Algorithms; Arabidopsis; Arabidopsis - chemistry; Arabidopsis - genetics; Arabidopsis - metabolism; Arabidopsis Proteins - analysis; Arabidopsis Proteins - genetics; Arabidopsis Proteins - metabolism; Bayes Theorem; Bioinformatics; Computation; Databases, Protein; Green Fluorescent Proteins - genetics; Localization; Mass Spectrometry; Mathematical models; Membrane Proteins - analysis; Position (location); Protein Interaction Mapping; Proteins; Proteome - analysis; Proteome - genetics; Proteome - metabolism; Software
• ISSN: 1367-4803; 1367-4811; 1367-4811; 1460-2059
• DOI: 10.1093/bioinformatics/btu550

Motivation: Knowing the subcellular location of proteins is critical for understanding their function and developing accurate networks representing eukaryotic biological processes. Many computational tools have been developed to predict proteome-wide subcellular location, and abundant experimental data from green fluorescent protein (GFP) tagging or mass spectrometry (MS) are available in the model plant, Arabidopsis. None of these approaches is error-free, and thus, results are often contradictory. Results: To help unify these multiple data sources, we have developed the SUBcellular Arabidopsis consensus (SUBAcon) algorithm, a naive Bayes classifier that integrates 22 computational prediction algorithms, experimental GFP and MS localizations, protein–protein interaction and co-expression data to derive a consensus call and probability. SUBAcon classifies protein location in Arabidopsis more accurately than single predictors. Availability: SUBAcon is a useful tool for recovering proteome-wide subcellular locations of Arabidopsis proteins and is displayed in the SUBA3 database (http://suba.plantenergy.uwa.edu.au). The source code and input data is available through the SUBA3 server (http://suba.plantenergy.uwa.edu.au//SUBAcon.html) and the Arabidopsis SUbproteome REference (ASURE) training set can be accessed using the ASURE web portal (http://suba.plantenergy.uwa.edu.au/ASURE). Contact:  cornelia.hooper@uwa.edu.au or ian.castleden@uwa.edu.au Supplementary information:  Supplementary data are available at Bioinformatics online.