title: Combining quantitative proteomics data processing workflows for greater sensitivity.
abstract: We here describe a normalization method to combine quantitative proteomics data. By merging the output of two popular quantification software packages, we obtained a 20% increase (on average) in the number of quantified human proteins without suffering from a loss of quality. Our integrative workflow is freely available through our user-friendly, open-source Rover software (http://compomics-rover.googlecode.com/).
authors.affiliation: Department of Medical Protein Research, Vlaams Instituut voor Biotechnologie (VIB), Ghent, Belgium.
authors.forename: Niklaas
authors.initials: N
authors.lastname: Colaert
authors.forename: Christophe
authors.initials: C
authors.lastname: Van Huele
authors.forename: Sven
authors.initials: S
authors.lastname: Degroeve
authors.forename: An
authors.initials: A
authors.lastname: Staes
authors.forename: Joël
authors.initials: J
authors.lastname: Vandekerckhove
authors.forename: Kris
authors.initials: K
authors.lastname: Gevaert
authors.forename: Lennart
authors.initials: L
authors.lastname: Martens
mesh_terms: D000465:Algorithms; D019295:Computational Biology; D030562:Databases, Protein; D001330:Electronic Data Processing / Q000379:methods*; D006801:Humans; D040901:Proteomics / Q000592:standards / Q000706:statistics & numerical data*; D011786:Quality Control; D012984:Software; D057188:Workflow