PepTraq: a toolbox for in silico data mining and fast sequence filtering

Area of Science:

• Bioinformatics
• Genomics
• Proteomics

Background:

• Advancements in de novo sequencing tools generate vast amounts of genomic and transcriptomic data from diverse animal models.
• Existing data analysis often requires multiple, scattered bioinformatics tools, hindering efficient processing.

Purpose of the Study:

• To develop a unified platform, PepTraq, that consolidates essential data analysis functionalities.
• To facilitate the identification and processing of sequences, particularly for non-annotated transcripts and mass spectrometry (MS) applications.

Main Methods:

• PepTraq integrates functionalities for sequence filtering based on multiple criteria.
• It supports tasks such as re-annotation, secretome and neuropeptidome extraction, and targeted peptide/protein searches.
• The tool prepares specific FASTA files for proteomics and peptidomics MS analyses and aids in MS data processing.

Main Results:

• PepTraq provides a comprehensive solution for analyzing large-scale genomic and transcriptomic datasets.
• It streamlines the workflow for identifying non-annotated transcripts and preparing data for MS.
• The integrated approach simplifies complex bioinformatics tasks.

Conclusions:

• PepTraq offers a powerful, integrated solution for researchers working with unconventional animal model data.
• Its functionalities enhance the efficiency of transcriptomic and proteomic data analysis, especially for MS-based studies.
• The tool is accessible as both a downloadable desktop application and a web application, with open-source code.