Tomasz Gambin | PubMed Health

PubMed2025

polars-bio-fast, scalable, and out-of-core operations on large genomic interval datasets.

MOTIVATION: Genomic studies very often rely on computationally intensive analyses of relationships between features, which are typically represented as intervals along a 1D coordinate system (such as positions on a chromosome). In this context, the Python programming language is extensively used for manipulating and analyzing data stored in a tabular form of rows and columns, called a DataFrame. Pandas is the most widely used Python DataFrame package and has been criticized for inefficiencies and scalability issues, which its modern alternative-Polars-aims to address with a native backend written in the Rust programming language. RESULTS: polars-bio is a Python library that enables fast, parallel and out-of-core operations on large genomic interval datasets. Its main components are implemented in Rust, using the Apache DataFusion query engine and Apache Arrow for efficient data representation. It is compatible with Polars and Pandas DataFrame formats. In a real-world comparison (107 versus 1.2×106 intervals), our library runs overlap queries 6.5×, nearest queries 15.5×, count_overlaps queries 38×, and coverage queries 15× faster than Bioframe. On equally sized synthetic sets (107 versus 107), the corresponding speedups are 1.6×, 5.5×, 6×, and 6×. In streaming mode, on real and synthetic interval pairs, our implementation uses 90× and 15× less memory for overlap, 4.5× and 6.5× less for nearest, 60× and 12× less for count_overlaps, and 34× and 7× less for coverage than Bioframe. Multi-threaded benchmarks show good scalability characteristics. To the best of our knowledge, polars-bio is the most efficient single-node library for genomic interval DataFrames in Python. AVAILABILITY AND IMPLEMENTATION: polars-bio is an open-source Python package distributed under the Apache License available for major platforms, including Linux, macOS, and Windows in the PyPI registry. The online documentation is https://biodatageeks.org/polars-bio/ and the source code is available on GitHub: https://github.com/biodatageeks/polars-bio and Zenodo: https://doi.org/10.5281/zenodo.16374290. are available at Bioinformatics online.

Software↗

PubMed2025

Ataxia and oculomotor apraxia caused by a large-scale deletion in the senataxin gene.

Senataxin, an RNA/DNA helicase, is a key protein providing genome stability and one of the best characterized R-loop-binding factors playing an important role in transcription and DNA repair processes. Pathogenic SETX gene variants cause autosomal recessive spinocerebellar ataxia with axonal neuropathy (AOA2, MIM #606002) and autosomal dominant juvenile amyotrophic lateral sclerosis (ALS4, MIM #602433), rare neurodegenerative disorders characterized by juvenile onset of progressive cerebellar ataxia, axonal sensorimotor peripheral neuropathy, combined upper and lower motor neuron symptoms, and increased serum alpha-fetoprotein (AFP; specific for AOA2). We report two cases of adult patients presenting with cerebellar syndrome, scanned speech, and exercise intolerance which started in the second/third decade of life and were followed by muscle weakness and impaired gait coordination. Whole exome sequencing (WES) was performed to analyze single nucleotide and copy number variants. A decreased coverage of a genomic region of around 16 kb on chromosome 9 (chr9:132,295,852-132,311,876), suggesting a deletion encompassing 5 exons of the SETX gene (exons 11-15, NM_015046.7) was observed. This homozygous SETX (9q34.13) deletion leads to a frame shift and consequently truncation of the helicase domain in the protein. Loss-of-function variants in the SETX gene are known to be pathogenic. Statistical analysis of NGS data from the Polish population identified a few heterozygous carriers, suggesting its region-specific origin.

Humans↗