Flexible and Accessible Workflows for Improved Proteogenomic Analysis Using the Galaxy Framework
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- 作者：Pratik D. Jagtap ; James E. Johnson ; Getiria Onsongo ; Fredrik W. Sadler ; Kevin Murray ; Yuanbo Wang ; Gloria M. Shenykman ; Sricharan Bandhakavi ; Lloyd M. Smith ; Timothy J. Griffin
- 刊名：Journal of Proteome Research
- 出版年：2014
- 出版时间：December 5, 2014
- 年：2014
- 卷：13
- 期：12
- 页码：5898-5908
- 全文大小：544K
- ISSN：1535-3907
文摘
Proteogenomics combines large-scale genomic and transcriptomic data with mass-spectrometry-based proteomic data to discover novel protein sequence variants and improve genome annotation. In contrast with conventional proteomic applications, proteogenomic analysis requires a number of additional data processing steps. Ideally, these required steps would be integrated and automated via a single software platform offering accessibility for wet-bench researchers as well as flexibility for user-specific customization and integration of new software tools as they emerge. Toward this end, we have extended the Galaxy bioinformatics framework to facilitate proteogenomic analysis. Using analysis of whole human saliva as an example, we demonstrate Galaxy鈥檚 flexibility through the creation of a modular workflow incorporating both established and customized software tools that improve depth and quality of proteogenomic results. Our customized Galaxy-based software includes automated, batch-mode BLASTP searching and a Peptide Sequence Match Evaluator tool, both useful for evaluating the veracity of putative novel peptide identifications. Our complex workflow (approximately 140 steps) can be easily shared using built-in Galaxy functions, enabling their use and customization by others. Our results provide a blueprint for the establishment of the Galaxy framework as an ideal solution for the emerging field of proteogenomics.