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Next-generation Sequencing03:00

Next-generation Sequencing

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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
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Updated: Jul 30, 2025

Novel Sequence Discovery by Subtractive Genomics
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SeqWiz: a modularized toolkit for next-generation protein sequence database management and analysis.

Ping Zhang1, Min Wang1, Tao Zhou2,3

  • 1Research Institute for Reproductive Medicine and Genetic Diseases, The Affiliated Wuxi Maternity and Child Health Care Hospital of Nanjing Medical University, Wuxi, 214002, China.

BMC Bioinformatics
|May 16, 2023
PubMed
Summary

SeqWiz is a new toolkit for creating advanced protein sequence databases and performing proteomic analyses. It introduces novel data formats (SQPD, SET) that significantly improve efficiency over traditional methods.

Keywords:
Protein sequence databaseSequence formatSequence processingSequence variationSmall open reading frame

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Computational Biology

Background:

  • Proteomic technologies are rapidly advancing, necessitating improvements in protein sequence databases and analysis software.
  • Current tools struggle to handle the complexity of sequence variations and modifications.

Purpose of the Study:

  • To develop a toolkit (SeqWiz) for constructing next-generation sequence databases.
  • To enable efficient proteomic-centric sequence analyses.
  • To introduce novel data formats for improved performance.

Main Methods:

  • Developed two new data formats: SQPD (SQLite-based local database) and SET (JSON-based entry lists).
  • Created open-source Python tools for UniProt data retrieval, format conversion, sequence generation, filtering, and analysis.
  • Implemented tools compatible with traditional FASTA and PEFF formats.

Main Results:

  • SQPD and SET formats demonstrated superior performance in time and resource consumption compared to FASTA/PEFF.
  • SeqWiz provides modular tools for database preparation and downstream analysis.
  • Source code is freely available on GitHub.

Conclusions:

  • SeqWiz offers a user-friendly solution for preparing sequence databases and conducting proteomic analyses.
  • The toolkit supports novel formats and traditional formats, facilitating proteoform analysis and precision proteomics.
  • SeqWiz is expected to advance proteomic standardization and software development.