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

Abstract

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 à These authors contributed equally to this work.

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“…Only peptides that were ranked one and scored above the threshold score, set at 99% confidence, were withheld. All further data management was done by ms_lims (Helsens et al, 2010).…”

Degradomics Reveals That Cleavage Specificity Profiles of Caspase-2 and Effector Caspases Are Alike

“…The false discovery rate, calculated as described before (45), was 3.37%. All peptide identifications were processed, stored, and managed using the ms_lims software (46). MS spectra and MS intensity profiles of neo-N-terminal peptides were individually inspected.…”

Exploring the potential of public proteomics data

“…The only real solution is to make it easier for submitters to provide additional information, or to annotate this information automatically in the standard file formats. This work has already started, notable in LIMS systems such as MASPECTRAS 121, ms_lims 122, and Proteios 123, but it will still take some time before it is straightforward to capture all the desired information.…”