BMC Bioinformatics (May 2023)

SeqWiz: a modularized toolkit for next-generation protein sequence database management and analysis

  • Ping Zhang,
  • Min Wang,
  • Tao Zhou,
  • Daozhen Chen

DOI
https://doi.org/10.1186/s12859-023-05334-9
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 9

Abstract

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Abstract Background Current proteomic technologies are fast-evolving to uncover the complex features of sequence processes, variations and modifications. Thus, protein sequence database and the corresponding softwares should also be improved to solve this issue. Results We developed a state-of-the-art toolkit (SeqWiz) for constructing next-generation sequence databases and performing proteomic-centric sequence analyses. First, we proposed two derived data formats: SQPD (a well-structured and high-performance local sequence database based on SQLite), and SET (an associated list of selected entries based on JSON). The SQPD format follows the basic standards of the emerging PEFF format, which also aims to facilitate the search of complex proteoform. The SET format is designed for generating subsets with with high-efficiency. These formats are shown to greatly outperform the conventional FASTA or PEFF formats in time and resource consumption. Then, we mainly focused on the UniProt knowledgebase and developed a collection of open-source tools and basic modules for retrieving species-specific databases, formats conversion, sequence generation, sequence filter, and sequence analysis. These tools are implemented by using the Python language and licensed under the GNU General Public Licence V3. The source codes and distributions are freely available at GitHub ( https://github.com/fountao/protwiz/tree/main/seqwiz ). Conclusions SeqWiz is designed to be a collection of modularized tools, which is friendly to both end-users for preparing easy-to-use sequence databases as well as bioinformaticians for performing downstream sequence analysis. Besides the novel formats, it also provides compatible functions for handling the traditional text based FASTA or PEFF formats. We believe that SeqWiz will promote the implementing of complementary proteomics for data renewal and proteoform analysis to achieve precision proteomics. Additionally, it can also drive the improvement of proteomic standardization and the development of next-generation proteomic softwares.

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