Publikation:

Protocol for sequence clustering with PaSiMap in Jalview

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Morell_2-15376ssaladgw0.pdf
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Datum

2025

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Procter, James
Barton, Geoffrey J.

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http://nbn-resolving.de/urn:nbn:de:bsz:352-2-15376ssaladgw0
DOI (zitierfähiger Link)
https://doi.org/10.1016/j.xpro.2025.103603
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CC BY-NC 4.0

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Open Access-Veröffentlichung
Open Access Gold

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Biologie: Publikationen
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Published

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STAR Protocols. Elsevier. 2025, 6(1), 103603. eISSN 2666-1667. Verfügbar unter: doi: 10.1016/j.xpro.2025.103603

Zusammenfassung

Pairwise similarity mapping (PaSiMap), implemented in Jalview, serves as an alternative to principal component analysis (PCA) for analyzing protein sequence relationships without requiring pre-computed multiple sequence alignments. It excels at distinguishing between systematic and random differences in datasets. Here, we present a protocol for sequence clustering with PaSiMap in Jalview. We describe steps for installation, sequence importing, and running PaSiMap analyses. We also detail procedures for plotting and data interpretation in RStudio, offering a streamlined approach for visualizing and analyzing protein sequence relationships effectively.

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570 Biowissenschaften, Biologie

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Datensatz
MorellThomas/plot_pasimap_data: Release linked to Star Protocols
(2024) Morell, Thomas; Procter, Jim

Zitieren

ISO 690MORELL, Thomas, James PROCTER, Geoffrey J. BARTON, Kay DIEDERICHS, Olga MAYANS, Jennifer R. FLEMING, 2025. Protocol for sequence clustering with PaSiMap in Jalview. In: STAR Protocols. Elsevier. 2025, 6(1), 103603. eISSN 2666-1667. Verfügbar unter: doi: 10.1016/j.xpro.2025.103603
BibTex
@article{Morell2025-03Proto-72601,
  title={Protocol for sequence clustering with PaSiMap in Jalview},
  year={2025},
  doi={10.1016/j.xpro.2025.103603},
  number={1},
  volume={6},
  journal={STAR Protocols},
  author={Morell, Thomas and Procter, James and Barton, Geoffrey J. and Diederichs, Kay and Mayans, Olga and Fleming, Jennifer R.},
  note={Article Number: 103603}
}
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