Protocol for sequence clustering with PaSiMap in Jalview
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.
Authors
- Kay Diederichs (ORCID: https://orcid.org/0000-0001-5360-0905)
- James B Procter (ORCID: https://orcid.org/0000-0002-7865-7382)
- Jennifer R. Fleming (ORCID: https://orcid.org/0000-0003-4016-8740)
- Olga Mayans (ORCID: https://orcid.org/0000-0001-6876-8532)
- Geoffrey J. Barton (ORCID: https://orcid.org/0000-0002-9014-5355)
- Thomas Morell
Institutions
- University of Dundee (GB)
- University of Konstanz (DE)
Publication Details
- Journal
- STAR Protocols
- Published
- 2025-02-26
- DOI
- https://doi.org/10.1016/j.xpro.2025.103603
- Citations
- 2
- Primary Topic
- Genomics and Phylogenetic Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.61
Funders
- Wellcome Trust