ProteoSign v2: a faster and evolved user-friendly online tool for statistical analyses of differential proteomics

被引:13
作者
Theodorakis, Evangelos [1 ,2 ]
Antonakis, Andreas N. [1 ]
Baltsavia, Ismini [1 ]
Pavlopoulos, Georgios A. [3 ]
Samiotaki, Martina [4 ]
Amoutzias, Grigoris D. [5 ]
Theodosiou, Theodosios [1 ]
Acuto, Oreste [6 ]
Efstathiou, Georgios [1 ,6 ]
Iliopoulos, Ioannis [1 ]
机构
[1] Univ Crete, Div Basic Sci, Med Sch, Iraklion 71110, Greece
[2] Tech Univ Munich, Dept Informat, Boltzmannstr 3, D-85748 Garching, Germany
[3] BSRC Alexander Fleming, Inst Fundamental Biomed Res, 34 Fleming St, Vari 16672, Greece
[4] BSRC Alexander Fleming, Inst Bioinnovat, 34 Fleming St, Vari 16672, Greece
[5] Univ Thessaly, Bioinformat Lab, Dept Biochem & Biotechnol, Larisa 41500, Greece
[6] Univ Oxford, Sir William Dunn Sch Pathol, South Parks Rd, Oxford OX1 3RE, England
关键词
CELL-CULTURE; AMINO-ACIDS; WEB SERVER; PROTEIN; IDENTIFICATION; TRANSLATION; NETWORKS;
D O I
10.1093/nar/gkab329
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Bottom-up proteomics analyses have been proved over the last years to be a powerful tool in the characterization of the proteome and are crucial for understanding cellular and organism behaviour. Through differential proteomic analysis researchers can shed light on groups of proteins or individual proteins that play key roles in certain, normal or pathological conditions. However, several tools for the analysis of such complex datasets are powerful, but hard-to-use with steep learning curves. In addition, some other tools are easy to use, but are weak in terms of analytical power. Previously, we have introduced ProteoSign, a powerful, yet user-friendly open-source online platform for protein differential expression/abundance analysis designed with the end-proteomics user in mind. Part of Proteosign's power stems from the utilization of the well-established Linear Models For Microarray Data (LIMMA) methodology. Here, we present a substantial upgrade of this computational resource, called ProteoSign v2, where we introduce major improvements, also based on user feedback. The new version offers more plot options, supports additional experimental designs, analyzes updated input datasets and performs a gene enrichment analysis of the differentially expressed proteins. We also introduce the deployment of the Docker technology and significantly increase the speed of a full analysis. ProteoSign v2 is available at http://bioinformatics.med. uoc.gr/ProteoSign.
引用
收藏
页码:W573 / W577
页数:5
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