title: Representation of selected-reaction monitoring data in the mzQuantML data standard.
abstract: The mzQuantML data standard was designed to capture the output of quantitative software in proteomics, to support submissions to public repositories, development of visualization software and pipeline/modular approaches. The standard is designed around a common core that can be extended to support particular types of technique through the release of semantic rules that are checked by validation software. The first release of mzQuantML supported four quantitative proteomics techniques via four sets of semantic rules: (i) intensity-based (MS(1) ) label free, (ii) MS(1) label-based (such as SILAC or N(15) ), (iii) MS(2) tag-based (iTRAQ or tandem mass tags), and (iv) spectral counting. We present an update to mzQuantML for supporting SRM techniques. The update includes representing the quantitative measurements, and associated meta-data, for SRM transitions, the mechanism for inferring peptide-level or protein-level quantitative values, and support for both label-based or label-free SRM protocols, through the creation of semantic rules and controlled vocabulary terms. We have updated the specification document for mzQuantML (version 1.0.1) and the mzQuantML validator to ensure that consistent files are produced by different exporters. We also report the capabilities for production of mzQuantML files from popular SRM software packages, such as Skyline and Anubis.
authors.affiliation: Institute of Integrative Biology, University of Liverpool, Liverpool, UK.
authors.forename: Da
authors.initials: D
authors.lastname: Qi
authors.affiliation: The Faculty of Life Sciences, University of Manchester, Manchester, UK.
authors.forename: Craig
authors.initials: C
authors.lastname: Lawless
authors.affiliation: Department of Immunotechnology, Lund University, Lund, Sweden.
authors.forename: Johan
authors.initials: J
authors.lastname: Teleman
authors.affiliation: Department of Immunotechnology, Lund University, Lund, Sweden.|Bioinformatics Infrastructure for Life Sciences (BILS), Lund University, Lund, Sweden.
authors.forename: Fredrik
authors.initials: F
authors.lastname: Levander
authors.affiliation: Institute of Integrative Biology, University of Liverpool, Liverpool, UK.
authors.forename: Stephen W
authors.initials: SW
authors.lastname: Holman
authors.affiliation: The Faculty of Life Sciences, University of Manchester, Manchester, UK.
authors.forename: Simon
authors.initials: S
authors.lastname: Hubbard
authors.affiliation: Institute of Integrative Biology, University of Liverpool, Liverpool, UK.
authors.forename: Andrew R
authors.initials: AR
authors.lastname: Jones
mesh_terms: D019295:Computational Biology / Q000379:methods* / Q000592:standards; D007553:Isotope Labeling / Q000379:methods / Q000592:standards; D013058:Mass Spectrometry / Q000379:methods* / Q000592:standards; D020543:Proteome / Q000032:analysis* / Q000378:metabolism / Q000592:standards; D040901:Proteomics / Q000379:methods* / Q000592:standards; D015203:Reproducibility of Results; D012984:Software
chemical_list: D020543:Proteome
keywords: Bioinformatics; Proteomics standards initiative; SRM; mzQuantML