Biology subjects

Gudys, A.

Publications and source records attributed to Gudys, A..

11 recordsLinked to original sources

bioRxiv2026

First community challenge for automated virus taxonomy

The rapid rate of virus discovery renders manual curation by taxonomy experts increasingly impractical, creating a need for reliable software that can reproducibly assign viral contigs to taxa at all fifteen ranks of the virus taxonomy. We led an open community challenge for the computational taxonomic classification of viruses and assembled a dataset of virus sequences combining expert-curated and metagenomic sequences. Seventeen teams contributed a total of thirty-four automated, fully reproducible classification pipelines. Most tools correctly assigned viruses belonging to established species, genera, or families, but viruses that are unclassified at those lower ranks remain challenging. This study provides datasets, open-source software, novel approaches, and recommendations to benchmark computational taxonomic classification of viruses, and support organizing the many viruses discovered in big omics data.

microbiology↗

bioRxiv2025

FAMSA2 enables accurate multiple sequence alignment at protein-universe scale

We introduce FAMSA2, an algorithm that produces high-accuracy multiple protein sequence alignments with unprecedented speed. Across structural, phylogenetic, and functional benchmarks, FAMSA2 matches or exceeds the accuracy of state-of-the-art tools while running up to 400 times faster and outperforming the fastest existing aligners. The ability of FAMSA2 to process 12 million sequences in 40 minutes on a 64 GB RAM workstation enables evolutionary and structural analyses at previously unattainable scales.

bioinformatics↗

bioRxiv2025

An nf-core framework for the systematic comparison of alternative modeling tools: the multiple sequence alignment case study

The computational complexity of many key bioinformatics problems has resulted in numerous alternative heuristic solutions, where no single approach consistently outperforms all others. This creates difficulties for users trying to identify the most suitable tool for their dataset and for developers managing and evaluating alternative methods. As data volumes grow, deploying these methods becomes increasingly difficult, highlighting the need for standardized frameworks for seamless tool deployment and comparison in HPC environments. Multiple sequence aligners (MSAs) rank among the most commonly employed modeling techniques in bioinformatics, playing a crucial role in applications such as protein structure prediction, phylogenetic reconstruction, and variant effect prediction. The NP-hardness of MSAs makes them a major example of problems where heuristics stand central, as no optimal solution can be currently obtained, within the limits of operational computational requirements. Here, we present a pilot design of an nf-core framework for streamlined tool deployment and rigorous performance evaluation focusing on the MSAs software ecosystem. By integrating the most popular MSA tools and focusing on a modular, and extensible architecture, we aspire to provide a key platform supporting MSA deployment, evaluation, and algorithmics development to the MSA community, and a proof-of-principle to the wider bioinformatics community.

bioinformatics↗

bioRxiv2024

Ultrafast and accurate sequence alignment and clustering of viral genomes

Viromics produces millions of viral genomes and fragments annually, overwhelming traditional sequence comparison methods. We introduce Vclust, a novel approach that determines average nucleotide identity by Lempel-Ziv parsing and clusters viral genomes with thresholds endorsed by authoritative viral genomics and taxonomy consortia. Vclust demonstrates superior accuracy and efficiency compared to existing tools, clustering millions of virus genomes in a few hours on a mid-range workstation.

bioinformatics↗

bioRxiv2024

Ultra-efficient, unified discovery from microbial sequencing with SPLASH and precise statistical assembly

Bacteria comprise > 12% of Earths biomass and profoundly impact human and planetary health.1 Many key biological functions of microbes, and functions differentiating strains, are conferred or modified by genome plasticity including mobilization of genetic elements, phage integration, and CRISPR arrays. Characterizing each of these processes is time-consuming and requires custom bioinformatic workflows ill-suited to enable discovery of new sources of genetic diversity or to uncover which elements are active. Further, strain typing of bacterial species and approaches to discriminate sub-populations remain time-consuming and resource intensive. Here, we show that SPLASH, our published approach for reference-free discovery and analysis directly from raw reads, and an improved statistical assembly algorithm, compactors, unify diverse tasks in microbial sequence analysis: discovering new mobile elements and CRISPR arrays missing from any reference, and generating rapid, metadata-free strain typing of diverse bacteria. SPLASH and compactors together constitute a new general discovery tool for biological discovery in the microbial world.

bioinformatics↗

bioRxiv2023

Efficient protein structure archiving using ProteStAr

MotivationThe introduction of Deep Minds Alpha Fold 2 enabled prediction of protein structures at unprecedented scale. AlphaFold Protein Structure Database and ESM Metagenomic Atlas contain hundreds of millions of structures stored in CIF and/or PDB formats. When compressed with a general-purpose utility like gzip, this translates to tens of terabytes of data which hinders the effective use of predicted structures in large-scale analyses. ResultsHere, we present ProteStAr, a compressor dedicated to CIF/PDB as well as, supplementary PAE files. Its main contribution is a novel approach to predict atom coordinates on the basis of the previously analyzed atoms. This allows efficient encoding of the coordinates which are the largest component of the protein structure files. By default, the compression is lossless, though the lossy mode with a controlled maximum error of coordinates reconstruction is also present. Compared to the competing packages, i.e., BinaryCIF, Foldcomp, PDC, our approach offers superior compression ratio at established reconstruction accuracy. By the efficient use of threads at both compression and decompression stages, the algorithm takes advantage of multicore architecture of current central processing units and operates with speeds about 1 GB/s. The presence of C++ API further increases the usability of the presented method. Availability and implementationThe source code of ProteStAr is available at https://github.com/refresh-bio/protestar.

bioinformatics↗

bioRxiv2021

PHIST: fast and accurate prediction of prokaryotichosts from metagenomic viral sequences

SummaryPHIST (Phage-Host Interaction Search Tool) predicts prokaryotic hosts of viruses from their genomic sequences. It improves host prediction accuracy at species level over current alignment-based tools (on average by 3 percentage points) as well as alignment-free and CRISPR-based tools (by 14-20 percentage points). PHIST is also two orders of magnitude faster than alignment-based tools making it suitable for metagenomics studies. Availability and implementationGNU-licensed C++ code wrapped in Python API available at: https://github.com/refresh-bio/phist Contactandrzej.zielezinski@amu.edu.pl, adam.gudys@polsl.pl Supplementary informationSupplementary data are available at publisher Web site.

bioinformatics↗

bioRxiv2021

CoLoRd: Compressing long reads

The costs of maintaining exabytes of data produced by sequencing experiments every year has become a major issue in todays genomics. In spite of the increasing popularity of the third generation sequencing, the existing algorithms for compressing long reads exhibit minor advantage over general purpose gzip. We present CoLoRd, an algorithm able to reduce 3rd generation sequencing data by an order of magnitude without affecting the accuracy of downstream analyzes.

bioinformatics↗

bioRxiv2019

Whisper 2: indel-sensitive short read mapping

SummaryWhisper 2 is a short-read-mapping software providing superior quality of indel variant calling. Its running times place it among the fastest existing tools. Availability and Implementationhttps://github.com/refresh-bio/whisper Contactsebastian.deorowicz@polsl.pl Supplementary informationSupplementary data are available at publishers Web site.

bioinformatics↗

bioRxiv2018

Kmer-db: instant evolutionary distance estimation

SummaryKmer-db is a new tool for estimating evolutionary relationship on the basis of k-mers extracted from genomes or sequencing reads. Thanks to an efficient data structure and parallel implementation, our software estimates distances between 40,715 pathogens in less than 4 minutes (on a modern workstation), 44 times faster than Mash, its main competitor.\n\nAvailability and Implementationhttps://github.com/refresh-bio/kmer-db\n\nContactsebastian.deorowicz@polsl.pl\n\nSupplementary informationSupplementary data are available at publishers Web site

bioinformatics↗

bioRxiv2017

Whisper: Read sorting allows robust mapping of sequencing data

MotivationMapping reads to a reference genome is often the first step in a sequencing data analysis pipeline. Mistakes made at this computationally challenging stage cannot be recovered easily.\n\nResultsWe present Whisper, an accurate and high-performant mapping tool, based on the idea of sorting reads and then mapping them against suffix arrays for the reference genome and its reverse complement. Employing task and data parallelism as well as storing temporary data on disk result in superior time efficiency at reasonable memory requirements. Whisper excels at large NGS read collections, in particular Illumina reads with typical WGS coverage. The experiments with real data indicate that our solution works in about 15% of the time needed by the well-known Bowtie2 and BWA-MEM tools at a comparable accuracy (validated in variant calling pipeline).\n\nAvailabilityWhisper is available for free from https://github.com/refresh-bio/Whisper or http://sun.aei.polsl.pl/REFRESH/Whisper/\n\nContactsebastian.deorowicz@polsl.pl\n\nSupplementary informationSupplementary data are available at publisher Web site.

bioinformatics↗