title: PROTEINCHALLENGE: crowd sourcing in proteomics analysis and software development.
abstract: In large-scale proteomics studies there is a temptation, after months of experimental work, to plug resulting data into a convenient-if poorly implemented-set of tools, which may neither do the data justice nor help answer the scientific question. In this paper we have captured key concerns, including arguments for community-wide open source software development and "big data" compatible solutions for the future. For the meantime, we have laid out ten top tips for data processing. With these at hand, a first large-scale proteomics analysis hopefully becomes less daunting to navigate. However there is clearly a real need for robust tools, standard operating procedures and general acceptance of best practises. Thus we submit to the proteomics community a call for a community-wide open set of proteomics analysis challenges--PROTEINCHALLENGE--that directly target and compare data analysis workflows, with the aim of setting a community-driven gold standard for data handling, reporting and sharing.
authors.affiliation: Kinetic Parameter Facility, Centre for Synthetic and Systems Biology-SynthSys, University of Edinburgh, UK.
authors.forename: Sarah F
authors.initials: SF
authors.lastname: Martin
authors.forename: Heiner
authors.initials: H
authors.lastname: Falkenberg
authors.forename: Thomas F
authors.initials: TF
authors.lastname: Dyrlund
authors.forename: Guennadi A
authors.initials: GA
authors.lastname: Khoudoli
authors.forename: Craig J
authors.initials: CJ
authors.lastname: Mageean
authors.forename: Rune
authors.initials: R
authors.lastname: Linding
mesh_terms: D019295:Computational Biology / Q000379:methods*; D040901:Proteomics / Q000379:methods*; D012985:Software Design