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Biology subjects

Vilain, M.

Publications and source records attributed to Vilain, M..

2 recordsLinked to original sources

dna-parser: a Python library written in Rust for fast encoding of DNA and RNA sequences

BackgroundThe ever-growing amount of available biological data leads modern analysis to be performed on large datasets. Unfortunately, bioinformatics tools for preprocessing and analyzing data are not always designed to treat such large amounts of data efficiently. Notably, this is the case when encoding DNA and RNA sequences into numerical representations, also called descriptors, before passing them to machine learning models. Furthermore, current Python tools available for this preprocessing step are not well suited to be integrated into pipelines resulting in slow encoding speeds. ResultsWe introduce dna-parser, a Python library written in Rust to encode DNA and RNA sequences into numerical features. The combination of Rust and Python allows to encode sequences rapidly and in parallel across multiple threads while maintaining compatibility with packages from the Python ecosystem. Moreover, this library implements many of the most widely used types of numerical feature schemes coming from bioinformaticss and natural language processing. Conclusiondna-parser is an easy to install Python library that offers many Python wheels for Linux (muslinux and manylinux), macOS, and Windows via pip (https://pypi.org/project/dna-parser/). The open source code is available on GitHub (https://github.com/Mvila035/dna_parser) along with the documentation (https://mvila035.github.io/dna_parser/documentation/).

bioinformatics↗

Global warming drives the evolutionary rate of H1N1 and H3N2 influenza viruses

The haemagglutinin (HA) and neuraminidase (NA) genes of seasonal influenza A evolve under continual immune-driven positive selection. To test whether the tempo of selection has changed over time, we mapped branch- and site-specific episodic diversifying selection (MEME) onto Bayesian relaxed-clock time trees for HA and NA in H1N1 and H3N2, across multiple countries and four sequence-subsampling schemes. We dated each selection episode and tested whether episodes accumulated through time after accounting for the growing number of sampled lineages. Positive-selection episodes increased over time in every gene-subtype combination, at about 2-6% per lineage-year, and rose faster for NA than HA. Episodes were concentrated at a small number of codon sites, especially recurrent sites in H3N2 HA that fell within canonical antigenic regions of the HA1 head. This increase was robust to subsampling scheme and time-bin width, and was driven disproportionately by recent lineages. A detrended spatial analysis found no association with latitude or temperature anomalies. Overall, positive selection on influenza surface antigens appears to be intensifying through time, most likely because of immune escape and expanded surveillance rather than climate warming.

evolutionary biology↗