PyKleeBarcode: Enabling representation of the whole animal kingdom in information space

As biological sequence databases continue growing, so do the insight that they promise to shed on the shape of the genetic diversity of life. However, to fulfil this promise the software must remain usable, be able to accommodate a large amount of data and allow use of modern high performance comput...

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Bibliographic Details
Published in:PloS one 2023-06, Vol.18 (6), p.e0286314-e0286314
Main Authors: Duchemin, Wandrille, Thaler, David S
Format: Article
Language:English
Subjects:
Animals
Bar codes
Biology and Life Sciences
Comparative analysis
Computation
Computer and Information Sciences
Evaluation
Evolution
Genetic analysis
Genetic diversity
Genomes
Graphical representations
Identification and classification
Indicators
Methods
Nucleotides
Open source software
Phylogenetics
Research and Analysis Methods
Software
Vectors (mathematics)
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Summary:As biological sequence databases continue growing, so do the insight that they promise to shed on the shape of the genetic diversity of life. However, to fulfil this promise the software must remain usable, be able to accommodate a large amount of data and allow use of modern high performance computing infrastructure. In this study we present a reimplementation as well as an extension of a technique using indicator vectors to compute and visualize similarities between sets of nucleotide sequences. We have a flexible and easy to use python program relying on standard and open-source libraries. Our tool allows analysis of very large complement of sequences using code parallelization, as well as by providing routines to split a computational task in smaller and manageable subtasks whose results are then merged. This implementation also facilitates adding new sequences into an indicator vector-based representation without re-computing the whole set. The efficient synthesis of data into knowledge is no trivial matter given the size and rapid growth of biological sequence databases. Based on previous results regarding the properties of indicator vectors, the open-source approach proposed here efficiently and flexibly supports comparative analysis of genetic diversity at a large scale. Our software is freely available at: https://github.com/WandrilleD/pyKleeBarcode.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0286314