Adrian Michael Altenhoff

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Altenhoff

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Adrian Michael

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0000-0001-7492-1273

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Publications1 - 10 of 15

Expanding the Orthologous Matrix (OMA) programmatic interfaces: REST API and the OmaDB packages for R and Python
Kaleb, Klara; Warwick Vesztrocy, Alex; Altenhoff, Adrian Michael; et al. (2019)
F1000Research
The Orthologous Matrix (OMA) is a well-established resource to identify orthologs among many genomes. Here, we present two recent additions to its programmatic interface, namely a REST API, and user-friendly R and Python packages called OmaDB. These should further facilitate the incorporation of OMA data into computational scripts and pipelines. The REST API can be freely accessed at https://omabrowser.org/api. The R OmaDB package is available as part of Bioconductor at http://bioconductor.org/packages/OmaDB/, and the omadb Python package is available from the Python Package Index (PyPI) at https://pypi.org/project/omadb/.
Linkage of atmospheric blocks and synoptic-scale Rossby waves: a climatological analysis
Altenhoff, Adrian Michael; Martius, Olivia; Croci-Maspoli, Mischa; et al. (2008)
Tellus A: Dynamic Meteorology and Oceanography
The link between atmospheric blocking and propagating and breaking synoptic-scale Rossby waves (termed PV streamers) are explored for the climatological period 1958–2002, using the ERA-40 re-analysis data. To this end, potential vorticity (PV) based climatologies of blocking and breaking waves are used, and features of the propagating waves is extracted from Hovm¨oller diagrams. The analyses cover the Northern Hemisphere during winter, and they are carried out for the Atlantic and Pacific basins separately. The results show statistically significant wave precursor signals, up to 5 d prior to the blocking onset. In the Atlantic, the precursor signal takes the form of a coherent wave train, emanating approximately 110◦ upstream of the blocking location. In the Pacific, a single long-lived (10 d) northerly velocity signal preludes the blocking onset. A spatial analysis is conducted of the location, frequency and form of breaking synoptic-scale Rossby waves, prior to the onset, during the lifetime and after the blocking decay. It reveals that cyclonic streamers are present to the southwest and anticyclonic streamers to the south and southeast, approximately 43% (36%) of the time in the Atlantic (Pacific) basin, and this is significantly above a climatological distribution.
OMA 2011: orthology inference among 1000 complete genomes
Altenhoff, Adrian Michael; Schneider, Adrian; Gonnet, Gaston H.; et al. (2011)
Nucleic Acids Research
OMA (Orthologous MAtrix) is a database that identifies orthologs among publicly available, complete genomes. Initiated in 2004, the project is at its 11th release. It now includes 1000 genomes, making it one of the largest resources of its kind. Here, we describe recent developments in terms of species covered; the algorithmic pipeline—in particular regarding the treatment of alternative splicing, and new features of the web (OMA Browser) and programming interface (SOAP API). In the second part, we review the various representations provided by OMA and their typical applications. The database is publicly accessible at http://omabrowser.org .
OMAMO: orthology-based alternative model organism selection
Nicheperovich, Alina; Altenhoff, Adrian Michael; Dessimoz, Christophe; et al. (2022)
Bioinformatics
The conservation of pathways and genes across species has allowed scientists to use non-human model organisms to gain a deeper understanding of human biology. However, the use of traditional model systems such as mice, rats and zebrafish is costly, time-consuming and increasingly raises ethical concerns, which highlights the need to search for less complex model organisms. Existing tools only focus on the few well-studied model systems, most of which are complex animals. To address these issues, we have developed Orthologous Matrix and Alternative Model Organism (OMAMO), a software and a web service that provides the user with the best noncomplex organism for research into a biological process of interest based on orthologous relationships between human and the species. The outputs provided by OMAMO were supported by a systematic literature review.
Inference of phylogenetic trees directly from raw sequencing reads using Read2Tree
Dylus, David; Altenhoff, Adrian Michael; Majidian, Sina; et al. (2024)
Nature Biotechnology
Current methods for inference of phylogenetic trees require running complex pipelines at substantial computational and labor costs, with additional constraints in sequencing coverage, assembly and annotation quality, especially for large datasets. To overcome these challenges, we present Read2Tree, which directly processes raw sequencing reads into groups of corresponding genes and bypasses traditional steps in phylogeny inference, such as genome assembly, annotation and all-versus-all sequence comparisons, while retaining accuracy. In a benchmark encompassing a broad variety of datasets, Read2Tree is 10-100 times faster than assembly-based approaches and in most cases more accurate-the exception being when sequencing coverage is high and reference species very distant. Here, to illustrate the broad applicability of the tool, we reconstruct a yeast tree of life of 435 species spanning 590 million years of evolution. We also apply Read2Tree to >10,000 Coronaviridae samples, accurately classifying highly diverse animal samples and near-identical severe acute respiratory syndrome coronavirus 2 sequences on a single tree. The speed, accuracy and versatility of Read2Tree enable comparative genomics at scale.
Parallel and Scalable Precise Clustering
Byma, Stuart; Dhasade, Akash; Altenhoff, Adrian Michael; et al. (2020)
PACT '20: Proceedings of the ACM International Conference on Parallel Architectures and Compilation Techniques
This paper describes a new technique for parallelizing protein clustering, an important bioinformatics computation for the analysis of protein sequences. Protein clustering identifies groups of proteins that are similar because they share long sequences of similar amino acids. Given a collection of protein sequences, clustering can significantly reduce the computational effort required to identify all similar sequences by avoiding many negative comparisons. The challenge, however, is to build a clustering that misses as few similar sequences (or elements, more generally) as possible. In this paper, we introduce precise clustering, a property that requires each pair of similar elements to appear together in at least one cluster. We show that transitivity in the data can be leveraged to merge clusters while maintaining a precise clustering, providing a basis for independently forming clusters. This allows us reformulate clustering as a bottom-up merge of independent clusters in a new algorithm called ClusterMerge. ClusterMerge exposes parallelism, enabling fast and scalable implementations. We apply ClusterMerge to find similar amino acid sequences in a collection o comparison, with only half as many comparisons. More importantly, ClusterMerge is highly amenable to parallel and distributed computation. Our implementation achieves a speedup of 604 times on 768 cores (1400 times faster than a comparable single-threaded clustering implementation), a strong scaling efficiency of 90%, and a weak scaling efficiency of nearly 100%. © 2020 Association for Computing Machinery.
New developments for the Quest for Orthologs benchmark service
Altenhoff, Adrian Michael; Nevers, Yannis; Tran, Vinh; et al. (2024)
NAR Genomics and Bioinformatics
The Quest for Orthologs (QfO) orthology benchmark service (https://orthology.benchmarkservice.org) hosts a wide range of standardized benchmarks for orthology inference evaluation. It is supported and maintained by the QfO consortium, and is used to gather ortholog predictions and to examine strengths and weaknesses of newly developed and existing orthology inference methods. The web server allows different inference methods to be compared in a standardized way using the same proteome data. The benchmark results are useful for developing new methods and can help researchers to guide their choice of orthology method for applications in comparative genomics and phylogenetic analysis. We here present a new release of the Orthology Benchmark Service with a new benchmark based on feature architecture similarity as well as updated reference proteomes. We further provide a meta-analysis of the public predictions from 18 different orthology assignment methods to reveal how they relate in terms of ortholog predictions and benchmark performance. These results can guide users of orthologs to the best suited method for their purpose.
Speeding up all-against-all protein comparisons while maintaining sensitivity by considering subsequence-level homology
Wittwer, Lucas D.; Piližota, Ivana; Altenhoff, Adrian Michael; et al. (2014)
PeerJ
Orthology inference and other sequence analyses across multiple genomes typically start by performing exhaustive pairwise sequence comparisons, a process referred to as “all-against-all”. As this process scales quadratically in terms of the number of sequences analysed, this step can become a bottleneck, thus limiting the number of genomes that can be simultaneously analysed. Here, we explored ways of speeding-up the all-against-all step while maintaining its sensitivity. By exploiting the transitivity of homology and, crucially, ensuring that homology is defined in terms of consistent protein subsequences, our proof-of-concept resulted in a 4× speedup while recovering >99.6% of all homologs identified by the full all-against-all procedure on empirical sequences sets. In comparison, state-of-the-art k-mer approaches are orders of magnitude faster but only recover 3–14% of all homologous pairs. We also outline ideas to further improve the speed and recall of the new approach. An open source implementation is provided as part of the OMA standalone software at http://omabrowser.org/standalone.
The Quest for Orthologs orthology benchmark service in 2022
Nevers, Yannis; Jones, Tamsin E. M.; Jyothi, Dushyanth; et al. (2022)
Nucleic Acids Research
The Orthology Benchmark Service evaluation, supported and maintained by the Quest for Orthologs consortium. It is an essential resource to compare existing and new methods of orthology inference (the bedrock for many comparative genomics and phylogenetic analysis) over a standard dataset and through common procedures. The Quest for Orthologs Consortium is dedicated to maintaining the resource up to date, through regular updates of the Reference Proteomes and increasingly accessible data through the OpenEBench platform. For this update, we have added a new benchmark based on curated orthology assertion from the Vertebrate Gene Nomenclature Committee, and provided an example meta-analysis of the public predictions present on the platform.
Quality assessment of gene repertoire annotations with OMArk
Nevers, Yannis; Warwick Vesztrocy, Alex; Rossier, Victor; et al. (2025)
Nature Biotechnology
In the era of biodiversity genomics, it is crucial to ensure that annotations of protein-coding gene repertoires are accurate. State-of-the-art tools to assess genome annotations measure the completeness of a gene repertoire but are blind to other errors, such as gene overprediction or contamination. We introduce OMArk, a software package that relies on fast, alignment-free sequence comparisons between a query proteome and precomputed gene families across the tree of life. OMArk assesses not only the completeness but also the consistency of the gene repertoire as a whole relative to closely related species and reports likely contamination events. Analysis of 1,805 UniProt Eukaryotic Reference Proteomes with OMArk demonstrated strong evidence of contamination in 73 proteomes and identified error propagation in avian gene annotation resulting from the use of a fragmented zebra finch proteome as a reference. This study illustrates the importance of comparing and prioritizing proteomes based on their quality measures.

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Adrian Michael Altenhoff

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