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J Extracell Vesicles. 2017 May 26;6(1):1321455. doi: 10.1080/20013078.2017.1321455. eCollection 2017.

A novel community driven software for functional enrichment analysis of extracellular vesicles data.

Author information

1
Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Australia.
2
Department of Computer Science and Information Technology, La Trobe University, Melbourne, Australia.
3
Department of Biopathology and Medical Biotechnologies, University of Palermo, Palermo, Italy.
4
The Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Australia.
5
Section of Allergy and Clinical Immunology, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA.
6
Bioinformatics Institute, ASTAR, Singapore, Singapore.
7
Children's Cancer and Blood Foundation Laboratories, Departments of Pediatrics, Cell and Developmental Biology, Drukier Institute for Children's Health, Meyer Cancer Center, Weill Cornell Medical College, New York, NY, USA.
8
Department of Medical Science, University of Torino, Medical School, Torino, Italy.
9
Division of Cancer and Genetics, School of Medicine, Cardiff University, Velindre Cancer Centre, Cardiff, UK.
10
Carlos Chagas Filho Institute of Biophysics, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
11
Division of Cancer Biology and Therapeutics, Departments of Surgery, Biomedical Sciences and Pathology and Laboratory Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
12
Exosomes Lab, Metabolomics Unit, CIC bioGUNE, CIBERehd. Bizkaia Technological Park, Derio 48160, Bikaia and IKERBASQUE Research Foundation, Bilbao, SPAIN.
13
Department of Oncology-Pathology, Cancer Centrum Karolinska, Karolinska Institutet and Karolinska University Hospital Solna, Stockholm, Sweden.
14
Department of Life Sciences, Pohang University of Science and Technology, Pohang, Republic of Korea.
15
Laboratory of Experimental Cancer Research, Department of Radiation Oncology and Experimental Cancer Research, Ghent University, Ghent, Belgium.
16
Department of Biochemistry and Cell Biology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.
17
Department of Biomedical and Biotechnological Sciences (BIOMETEC), University of Catania, Catania, Italy.
18
Department of Clinical Neurosciences, Wellcome Trust-Medical Research Council Stem Cell Institute and National Institute for Health Research Biomedical Research Centre, University of Cambridge, Cambridge, UK.
19
Laboratory for Medical Mass Spectrometry, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
20
Princess Margaret Cancer Centre, Toronto, Canada.
21
Institut Curie, PSL Research University, INSERM U932, Paris, France.
22
European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK.
23
Cardiovascular Research Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
24
Department of Molecular Cell Biology, Institute for Cancer Research, Oslo University Hospital-The Norwegian Radium Hospital, Oslo, Norway.
25
Centre for Cancer Biomedicine, Faculty of Medicine, University of Oslo, Oslo, Norway.
26
Krefting Research Centre, Institute of Medicine at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
27
Department of Transplantation, Mayo Clinic, Jacksonville, FL, USA.
28
Microenvironment and Metastasis Group, Department of Molecular Oncology, Spanish National Cancer Research Center (CNIO), Madrid, Spain.
29
Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
30
Department of Biomedical Sciences, Cardiff School of Health Sciences, Cardiff Metropolitan University, Cardiff, UK.

Abstract

Bioinformatics tools are imperative for the in depth analysis of heterogeneous high-throughput data. Most of the software tools are developed by specific laboratories or groups or companies wherein they are designed to perform the required analysis for the group. However, such software tools may fail to capture "what the community needs in a tool". Here, we describe a novel community-driven approach to build a comprehensive functional enrichment analysis tool. Using the existing FunRich tool as a template, we invited researchers to request additional features and/or changes. Remarkably, with the enthusiastic participation of the community, we were able to implement 90% of the requested features. FunRich enables plugin for extracellular vesicles wherein users can download and analyse data from Vesiclepedia database. By involving researchers early through community needs software development, we believe that comprehensive analysis tools can be developed in various scientific disciplines.

KEYWORDS:

Extracellular vesicles; FunRich; bioinformatics

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