Abstract
BackgroundEfficient analysis of results from mass spectrometry-based proteomics experiments requires access to disparate data types, including native mass spectrometry files, output from algorithms that assign peptide sequence to MS/MS spectra, and annotation for proteins and pathways from various database sources. Moreover, proteomics technologies and experimental methods are not yet standardized; hence a high degree of flexibility is necessary for efficient support of high- and low-throughput data analytic tasks. Development of a desktop environment that is sufficiently robust for deployment in data analytic pipelines, and simultaneously supports customization for programmers and non-programmers alike, has proven to be a significant challenge.ResultsWe describe multiplierz, a flexible and open-source desktop environment for comprehensive proteomics data analysis. We use this framework to expose a prototype version of our recently proposed common API (mzAPI) designed for direct access to proprietary mass spectrometry files. In addition to routine data analytic tasks, multiplierz supports generation of information rich, portable spreadsheet-based reports. Moreover, multiplierz is designed around a "zero infrastructure" philosophy, meaning that it can be deployed by end users with little or no system administration support. Finally, access to multiplierz functionality is provided via high-level Python scripts, resulting in a fully extensible data analytic environment for rapid development of custom algorithms and deployment of high-throughput data pipelines.ConclusionCollectively, mzAPI and multiplierz facilitate a wide range of data analysis tasks, spanning technology development to biological annotation, for mass spectrometry-based proteomics research.
Highlights
Efficient analysis of results from mass spectrometry-based proteomics experiments requires access to disparate data types, including native mass spectrometry files, output from algorithms that assign peptide sequence to MS/MS spectra, and annotation for proteins and pathways from various database sources
Task specific Windows desktop applications such as MSQuant [2] and InsilicosViewer [3] can access a subset of native mass spectrometry data files directly and provide flexibility through adjustable parameters, but are not readily extended across the full spectrum of data analytic activities required in modern proteomics research
To address the full spectrum of analyses, open source projects such as The OpenMS Proteomics Pipeline (TOPP) [4] and ProteoWizard [5] offer a set of modular tools for generation of pipelines
Summary
We demonstrate the functionality of multiplierz through relevant examples based on data and results from work in our laboratory. Given the acutely low levels of tyrosine phosphorylation in embryonic stem cells, we chose instead to gauge enrichment efficiency based on the relative fraction of MS/MS scans that contained a phosphotyrosine immonium ion (m/z = 216.04) [21,22], irrespective of any putative peptide sequence assignment. This strategy allowed us to readily decouple low overall peptide yield from poor enrichment of phosphotyrosine containing peptides in experiments that generally provided modest numbers of http://www.biomedcentral.com/1471-2105/10/364 a FLOW
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