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A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

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PGTools: A Software Suite for Proteogenomic Data Analysis and Visualization.

Shivashankar H Nagaraj, Nicola Waddell, Anil K Madugundu¹

¹∥Institute of Bioinformatics, International Technology Park, Bangalore 560 066, India.

Journal of Proteome Research

|March 12, 2015

Summary

This summary is machine-generated.

PGTools is a new open-source software suite that simplifies proteogenomic data analysis. It aids in identifying novel cancer-related proteins and enhances proteomic research, including large-scale projects like the Human Proteome Project.

Keywords:

RNA-seq automated workflows cancer mass spectrometry mutated peptides noncoding RNA proteogenomics pseudogenes

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Area of Science:

Bioinformatics
Proteomics
Genomics

Background:

Proteogenomic data analysis requires integrated approaches for mass spectrometry, proteomics, and genomics.
Existing tools may not efficiently handle the complexity of combined proteomic and genomic datasets.

Purpose of the Study:

To introduce PGTools, an open-source software suite designed for comprehensive proteogenomic data analysis and visualization.
To provide a unified platform for analyzing mass spectrometry data with genomic context.

Main Methods:

PGTools integrates applications, libraries, and customized databases for analyzing mass spectrometry data.
It automates tasks such as database searching, false discovery rate calculation, protein annotation, and peptide database generation from RNA-Seq transcripts.
Sophisticated visualization tools are employed for genome-scale peptide datasets.

Main Results:

PGTools successfully identified 203 novel protein coding regions in a colorectal cancer dataset, which were missed by conventional proteomic methods.
Experimental validation confirmed a subset of proteogenomic peptides in human PANC-1 cells.
The software demonstrated utility in identifying altered proteins associated with cancer.

Conclusions:

PGTools offers a powerful, streamlined solution for proteogenomic data analysis and visualization.
It is beneficial for individual research and large-scale initiatives like the chromosome-centric Human Proteome Project (C-HPP).
The software facilitates the discovery of novel protein-coding regions and enhances cancer proteogenomic studies.