OpenMS – An open-source software framework for mass spectrometry

Sturm, Marc; Bertsch, Andreas; Gröpl, Clemens; Hildebrandt, Andreas; Hussong, René; Lange, Eva; Pfeifer, Nico; Schulz-Trieglaff, Ole; Zerck, Alexandra; Reinert, Knut; Kohlbacher, Oliver

doi:10.1186/1471-2105-9-163

Cited by 592 publications

(492 citation statements)

References 32 publications

Supporting

Mentioning

489

Contrasting

Unclassified

Order By: Relevance

“…In contrast to existing web-based tools such as MASPECTRAS [4] or CPAS [5], ms_lims embraces a client-server architecture, which allows for more dynamic interaction. Additionally, ms_lims also differs from libraries such as OpenMS [6] in that the main focus lies on automation and data storage, rather than on data processing algorithms. Originally designed to support high-throughput, gel-free proteomics analyses, ms_lims uses identified peptides ('identification') as the core of its information structure.…”

mentioning

confidence: 99%

ms_lims, a simple yet powerful open source laboratory information management system for MS‐driven proteomics

et al. 2010

View full text Add to dashboard Cite

MS-based proteomics produces large amounts of mass spectra that require processing, identification and possibly quantification before interpretation can be undertaken. Highthroughput studies require automation of these various steps, and management of the data in association with the results obtained. We here present ms_lims (http://genesis.UGent.be/ ms_lims), a freely available, open-source system based on a central database to automate data management and processing in MS-driven proteomics analyses. Keywords:Bioinformatics / Data management / Laboratory information management system / Mascot / MS Proteomics labs nowadays often acquire hundreds of thousands to millions of MS/MS spectra per proteome analysis to make large-scale (comprehensive) proteome maps [1]. They rely on contemporary mass spectrometers with rapid duty cycles that increase the amount of produced data by a full order of magnitude compared to older instruments [2]. Automating the processing of these data, and managing their provenance has correspondingly become an important postanalysis task. The automation of these tasks requires the implementation of a start-to-end workflow around a central database management system that is designed for proteomics experiments, with some of the most prominent commercial and academic systems recently reviewed in [3]. Typical actions include collecting and warehousing MS/MS peak lists (often acquired on multiple, different instruments), assigning the accumulated MS/MS data to peptide identifications, quantifying peptides and proteins from MS or MS/MS data, and organizing both data and analysis results in a navigable project structure. In most high-throughput environments, these diverse actions are typically undertaken by different individuals, which further necessitates a role-based implementation of the software interfaces [4].To tackle and manage these problems associated with MSdriven proteomics, we developed ms_lims, an open source and instrument vendor-independent system for proteomics data management. In contrast to existing web-based tools such as MASPECTRAS [4] or CPAS [5], ms_lims embraces a client-server architecture, which allows for more dynamic interaction. Additionally, ms_lims also differs from libraries Abbreviations: LIMS, laboratory information management system; MGF, Mascot generic file; SQL, Structured Query Language Ã These authors contributed equally to this work.

show abstract

mentioning

confidence: 99%

ms_lims, a simple yet powerful open source laboratory information management system for MS‐driven proteomics

et al. 2010

View full text Add to dashboard Cite

show abstract

“…The mass-spectrometric data analysis is automated and implemented into a workflow that is based on OpenMS software [45,46] in combination with the freely available search engine OMSSA [47]. An extended description of the database analysis is available in [25], and a step-by-step tutorial is available in the supplementary files of that reference; the tutorial explains in detail how to prepare raw mass-spectrometric files for the dedicated database search.…”

Section: Discussionmentioning

confidence: 99%

Analysis of protein–RNA interactions in CRISPR proteins and effector complexes by UV-induced cross-linking and mass spectrometry

Sharma

Hrle

Kramer

et al. 2015

Methods

Self Cite

View full text Add to dashboard Cite

a b s t r a c tRibonucleoprotein (RNP) complexes play important roles in the cell by mediating basic cellular processes, including gene expression and its regulation. Understanding the molecular details of these processes requires the identification and characterization of protein-RNA interactions. Over the years various approaches have been used to investigate these interactions, including computational analyses to look for RNA binding domains, gel-shift mobility assays on recombinant and mutant proteins as well as co-crystallization and NMR studies for structure elucidation. Here we report a more specialized and direct approach using UV-induced cross-linking coupled with mass spectrometry. This approach permits the identification of cross-linked peptides and RNA moieties and can also pin-point exact RNA contact sites within the protein. The power of this method is illustrated by the application to different singleand multi-subunit RNP complexes belonging to the prokaryotic adaptive immune system, CRISPR-Cas (CRISPR: clustered regularly interspaced short palindromic repeats; Cas: CRISPR associated). In particular, we identified the RNA-binding sites within three Cas7 protein homologs and mapped the cross-linking results to reveal structurally conserved Cas7 -RNA binding interfaces. These results demonstrate the strong potential of UV-induced cross-linking coupled with mass spectrometry analysis to identify RNA interaction sites on the RNA binding proteins.

show abstract

“…OpenMS is flexible and powerful open source software for constructing analysis pipelines for proteomics 28. There is planned native support in OpenMS longer term for mzQuantML as an input and output format, but to date, there is no released converter for taking label‐free results in OpenMS and converting to mzQuantML.…”

Section: Methodsmentioning

confidence: 99%

The mzqLibrary – An open source Java library supporting the HUPO‐PSI quantitative proteomics standard

Zhang

Fan

et al. 2015

Proteomics

View full text Add to dashboard Cite

The mzQuantML standard has been developed by the Proteomics Standards Initiative for capturing, archiving and exchanging quantitative proteomic data, derived from mass spectrometry. It is a rich XML‐based format, capable of representing data about two‐dimensional features from LC‐MS data, and peptides, proteins or groups of proteins that have been quantified from multiple samples. In this article we report the development of an open source Java‐based library of routines for mzQuantML, called the mzqLibrary, and associated software for visualising data called the mzqViewer. The mzqLibrary contains routines for mapping (peptide) identifications on quantified features, inference of protein (group)‐level quantification values from peptide‐level values, normalisation and basic statistics for differential expression. These routines can be accessed via the command line, via a Java programming interface access or a basic graphical user interface. The mzqLibrary also contains several file format converters, including import converters (to mzQuantML) from OpenMS, Progenesis LC‐MS and MaxQuant, and exporters (from mzQuantML) to other standards or useful formats (mzTab, HTML, csv). The mzqViewer contains in‐built routines for viewing the tables of data (about features, peptides or proteins), and connects to the R statistical library for more advanced plotting options. The mzqLibrary and mzqViewer packages are available from https://code.google.com/p/mzq‐lib/.

show abstract

OpenMS – An open-source software framework for mass spectrometry

Cited by 592 publications

References 32 publications

ms_lims, a simple yet powerful open source laboratory information management system for MS‐driven proteomics

ms_lims, a simple yet powerful open source laboratory information management system for MS‐driven proteomics

Analysis of protein–RNA interactions in CRISPR proteins and effector complexes by UV-induced cross-linking and mass spectrometry

The mzqLibrary – An open source Java library supporting the HUPO‐PSI quantitative proteomics standard

Contact Info

Product

Resources

About