Dataset Information

A multicenter study benchmarks software tools for label-free proteome quantification.

ABSTRACT: Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test data sets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation-window setups. For consistent evaluation, we developed LFQbench, an R package, to calculate metrics of precision and accuracy in label-free quantitative MS and report the identification performance, robustness and specificity of each software tool. Our reference data sets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.

SUBMITTER: Navarro P

PROVIDER: S-EPMC5120688 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A multicenter study benchmarks software tools for label-free proteome quantification.

Navarro Pedro P Kuharev Jörg J Gillet Ludovic C LC Bernhardt Oliver M OM MacLean Brendan B Röst Hannes L HL Tate Stephen A SA Tsou Chih-Chiang CC Reiter Lukas L Distler Ute U Rosenberger George G Perez-Riverol Yasset Y Nesvizhskii Alexey I AI Aebersold Ruedi R Tenzer Stefan S

Nature biotechnology 20161003 11

Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DI ...[more]

PMID: 27701404

Similar Datasets

Project description:Scientific services in the area of OMICS research is becoming increasingly popular. In gen- eral omics research can produce a massive amount of data that can pose a challenge for computing infrastructure. While in the genomics area, many applications can run on Linux nodes the situation in proteomics is different. In proteomics, many applications are optimized to run on Windows computer only. As a sci- entific service provider, a core facility needs reliable, reproducible and easy to use integrated solutions. Liquid chromatography mass spectrometry intensity based label-free quantifica- tion using data-dependent acquisition is a popular approach in proteomics to perform relative quantification of proteins in complex samples. MaxQuant is a widely used software for this type of analysis which has a complex graphical user interface and provides information-rich outputs. We run it in which also includes Scaffold for search result validation and visualization and an R based quality control report generation. Data analysis workflows consists of several components: a workflow engine, compute hosts, and archives. In particular, applications can run on compute hosts, while the data is kept in an archive server. Therefore, the input and output need to be staged to the compute host and the results need to be staged back to the archive. This complexity can be overwhelming for a most common user. These different components have all been integrated into a robust and user-friendly application to process standardized label-free quantification experiments. We integrated MaxQuant as an in-house Software as a Service application so it can be used by any workflow engine in a platform-independent manner. In this manuscript, we provide a technical description of how MaxQuant as software service has been integrated into our heterogeneous compute environment for reproducible and automatic large scale high throughput data processing of label-free quantification experiments. In this Pride dataset we provide four raw files along with the full MaxQuant results, the Scaffold file, the QC-pdf report to have a concrete idea of the potential of our workflow. These data are generated in the FGCZ-course in Nov. 2016 (for further information see: http://www.fgcz.ch/education/genomics-courses01.html).

Dataset Information

A multicenter study benchmarks software tools for label-free proteome quantification.

Publications

A multicenter study benchmarks software tools for label-free proteome quantification.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets