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bioRxiv · 10.1101/320887

MS-PyCloud: An open-source, cloud computing-based pipeline for LC-MS/MS data analysis

Chen, L.·Zhang, B.·Schnaubelt, M.·Shah, P.·Aiyetan, P.·Chan, D.·Zhang, H.·Zhang, Z.
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Abstract

Rapid development and wide adoption of mass spectrometry-based proteomics technologies have empowered scientists to study proteins and their modifications in complex samples on a large scale. This progress has also created unprecedented challenges for individual labs to store, manage and analyze proteomics data, both in the cost for proprietary software and high-performance computing, and the long processing time that discourages on-the-fly changes of data processing settings required in explorative and discovery analysis. We developed an open-source, cloud computing-based pipeline, MS-PyCloud, with graphical user interface (GUI) support, for LC-MS/MS data analysis. The major components of this pipeline include data file integrity validation, MS/MS database search for spectral assignment, false discovery rate estimation, protein inference, determination of protein post-translation modifications, and quantitation of specific (modified) peptides and proteins. To ensure the transparency and reproducibility of data analysis, MS-PyCloud includes open source software tools with comprehensive testing and versioning for spectrum assignments. Leveraging public cloud computing infrastructure via Amazon Web Services (AWS), MS-PyCloud scales seamlessly based on analysis demand to achieve fast and efficient performance. Application of the pipeline to the analysis of large-scale iTRAQ/TMT LC-MS/MS data sets demonstrated the effectiveness and high performance of MS-PyCloud. The software can be downloaded at: https://bitbucket.org/mschnau/ms-pycloud/downloads/

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Chen, L., Zhang, B., Schnaubelt, M., Shah, P., Aiyetan, P., Chan, D., Zhang, H., Zhang, Z.. 2018-05-13. MS-PyCloud: An open-source, cloud computing-based pipeline for LC-MS/MS data analysis. https://doi.org/10.1101/320887

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