Back to Search Start Over

ProFeatMap: a highly customizable tool for 2D feature representation of protein sets.

Authors :
Bich G
Monsellier E
Travé G
Nominé Y
Source :
Bioinformatics advances [Bioinform Adv] 2023 Mar 09; Vol. 3 (1), pp. vbad022. Date of Electronic Publication: 2023 Mar 09 (Print Publication: 2023).
Publication Year :
2023

Abstract

Motivation: Studies of sets of proteins are a central point in biology. In particular, the application of omics in the last decades has generated lists of several hundreds or thousands of proteins or genes. However, these lists are often not inspected globally, possibly due to the lack of tools capable of simultaneously visualizing the feature architectures of a large number of proteins.<br />Results: Here, we present ProFeatMap, an intuitive Python-based website. For a given set of proteins, it allows to display features such as domains, repeats, disorder or post-translational modifications and their organization along the sequences, into a highly customizable 2D map. Starting from a user-defined protein list of UniProt accession codes, ProFeatMap extracts the most important annotated features available for each protein from one of the well-established databases such as Uniprot or InterPro, allocates shapes and colors, potentially depending on quantitative or qualitative data and sorts the protein list based on homologous feature content. The resulting publication-quality map allows even large protein families to be explored, and to classify them based on shared features. It can help to gain insights, for example, feature redundancy or feature pattern, that were previously overlooked. ProFeatMap is freely available on the web at: https://profeatmap.pythonanywhere.com/.<br />Availability and Implementation: Source code is freely accessible at https://github.com/profeatmap/ProFeatMap under the GPL license.<br />Supplementary Information: Supplementary data are available at Bioinformatics Advances online.<br /> (© The Author(s) 2023. Published by Oxford University Press.)

Details

Language :
English
ISSN :
2635-0041
Volume :
3
Issue :
1
Database :
MEDLINE
Journal :
Bioinformatics advances
Publication Type :
Academic Journal
Accession number :
36936371
Full Text :
https://doi.org/10.1093/bioadv/vbad022