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

Bruno Zanuttini1, Joël Henry2, Christophe Couronne3

  • 1Normandie Univ., Unicaen, CNRS UMR 6072, Ensicaen; GREYC, 14 000, Caen, France. bruno.zanuttini@unicaen.fr.

Amino Acids
|March 8, 2023
PubMed
Summary

PepTraq is a new bioinformatics tool that integrates multiple functions for analyzing genomic and transcriptomic data from unconventional animal models. It aids in identifying novel transcripts and preparing data for mass spectrometry (MS) applications.

Keywords:
Data processingIn silico analysisProteomicsSequence filteringTranscriptome

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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.