Flexible and Accessible Workflows for Improved Proteogenomic Analysis Using the Galaxy Framework

Abstract

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’s 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.

Improve your Galaxy text life: The Query Tabular Tool

“…The veracity of putative variant sequences matched to MS/MS spectra must be confirmed, which can be accomplished by querying the variant peptide sequences against NCBI’s non-redundant (nr) protein database using the BLASTP tool, which is implemented in Galaxy 4 . Those peptides which do not have a 100% alignment and sequence match to known sequences within the database qualify as verified variant sequences, which are then passed on for further analysis 3, 4 .…”

“…One example is emerging “multi-omic” analyses, which integrate software from different ‘omic domains and are well suited to the strengths of Galaxy 2 . For example, proteogenomics integrates tools for RNA-Seq assembly and analysis, software for matching tandem mass spectrometry (MS/MS) data to peptide and protein sequences, and other customized tools to characterize novel, variant protein sequences expressed within a sample 3, 4 . To enable compatibility between the software tools composing a proteogenomics workflow, tabular files often must be manipulated into appropriate formats recognized by specific tools.…”

An Accessible Proteogenomics Informatics Resource for Cancer Researchers

“…Galaxy enables integration of disparate, multi-omic tools in a single, user-friendly environment, as required for proteogenomics. (6,9,10) The new resource described here provides workflows and training in the most critical aspects of proteogenomics: generation of customized protein sequence databases from RNA-Seq data, matching of MS/MS data to putative variant peptide sequences, and confirmation of the novelty of these identified sequences.…”

JUMPg: An Integrative Proteogenomics Pipeline Identifying Unannotated Proteins in Human Brain and Cancer Cells

“…10, 20–22 The whole process can be laborious and error-prone. A number of computational methods have been proposed for generating customized database in recent years, 23–33 which can be classified into three categories: (i) DNA polymorphism/mutation (hereafter using “mutation” for simplicity) database, (ii) splice junction database, and (iii) genome/transcriptome six-frame translation (6FT) database for detecting non-canonical translation events in unknown coding DNA sequence regions.…”