Biology subjects

Suetake, H.

Publications and source records attributed to Suetake, H..

6 recordsLinked to original sources

bioRxiv2026

The GA4GH Workflow Execution Service: A Standard API for Workflow Execution and Management in Genomics

Rapid growth in life science data generation has led to large and increasingly distributed collections of sensitive genomic data. To analyse this data, researchers increasingly rely on computational workflows to enable scalable, portable and reproducible analysis. However, these workflows are executed by specialized workflow engines across heterogeneous compute environments, each with its own requirements. As a result, users often need engine- and compute-environment-specific knowledge to submit, monitor and manage workflow execution, increasing the barriers to interoperability. These challenges are compounded in large-scale projects, where workflow runs must be dispatched to local clusters, cloud platforms or data hosting infrastructures with different underlying technologies. We describe the Global Alliance for Genomics and Health (GA4GH) Workflow Execution Service (WES) API, an approved GA4GH standard first released in 2018, together with its data model and the endpoints that define a unified interface for workflow execution. By standardizing workflow invocation, the WES API allows a single client to submit, monitor and cancel workflow runs across diverse workflow engines and compute backends, such as scheduling clusters or cloud platforms. We surveyed thirteen adoptions of the standard, covering standalone services and platforms in four programming languages. In a two-site demonstration, a WES implementation from Germany and one from Japan executed the same federated allele-frequency analysis with site-specific adjustments and only aggregated results leaving either site, demonstrating that it is possible to run the same analysis across independently built and operated WES services in different countries. From the gaps identified, we propose extensions for community discussion.

bioinformatics↗

bioRxiv2026

Rapid chromosomal rearrangements and sex chromosome turnover underlie the evolution of parapatric Pacific Scomber mackerels

Teleost display remarkable species diversity despite relatively conserved karyotypes, suggesting an important role for chromosomal rearrangements in speciation. Yet this hypothesis remains poorly tested in pelagic marine fishes, as genomic studies have predominantly focused on freshwater and coastal taxa. In this study, we investigated the genomic basis of hybrid incompatibility between two parapatric Pacific mackerels, Scomber japonicus and S. australasicus, hypothesizing chromosomal rearrangements as the major driving forces. We generated haplotype-resolved de novo genome assemblies for both Pacific species and assessed genomic rearrangements along with the genome of the Atlantic species, S. scombrus, reconstructed from publicly available data. Comparative genomic analyses revealed extensive chromosomal rearrangements across the genomes. Notably, the rate of chromosomal inversions was approximately sevenfold higher between the two Pacific species than between allopatric lineages. These rearrangements included complex structural changes involving megabase-scale inversions and associated translocations. Our analyses also showed that the sex chromosomes of the three species evolved independently. In the two Pacific species, large recombination-suppression regions (>10 Mb) arose convergently but through distinct mechanisms: tandem chromosomal inversions in S. japonicus and, most likely, transposable element-mediated sequence divergence in S. australasicus. By contrast, recombination suppression in S. scombrus is restricted to a [~]14 kb hemizygous region containing amhr2Y, generated by duplication and translocation. Population-level analyses further revealed ongoing evolution of recombination-suppressed regions in the Pacific species and uncovered multiple Y chromosome lineages in S. australasicus that differ markedly in the extent of recombination suppression. Together, these results demonstrate rapid structural genome evolution in Scomber and provide a genomic framework for understanding how chromosomal rearrangements contribute to reproductive isolation, sex chromosome turnover, and the diversification of pelagic marine fishes.

evolutionary biology↗

bioRxiv2022

A workflow reproducibility scale for automatic validation of biological interpretation results.

BackgroundReproducibility of data analysis workflow is a key issue in the field of bioinformatics. Recent computing technologies, such as virtualization, have made it possible to reproduce workflow execution with ease. However, the reproducibility of results is not well discussed; that is, there is no standard way to verify whether the biological interpretation of reproduced results are the same. Therefore, it still remains a challenge to automatically evaluate the reproducibility of results. ResultsWe propose a new metric, a reproducibility scale of workflow execution results, to evaluate the reproducibility of results. This metric is based on the idea of evaluating the reproducibility of results using biological feature values (e.g., number of reads, mapping rate, and variant frequency) representing their biological interpretation. We also implemented a prototype system that automatically evaluates the reproducibility of results using the proposed metric. To demonstrate our approach, we conducted an experiment using workflows used by researchers in real research projects and the use cases that are frequently encountered in the field of bioinformatics. ConclusionsOur approach enables automatic evaluation of the reproducibility of results using a fine-grained scale. By introducing our approach, it is possible to evolve from a binary view of whether the results are superficially identical or not to a more graduated view. We believe that our approach will contribute to more informed discussion on reproducibility in bioinformatics.

bioinformatics↗

bioRxiv2022

Workflow sharing with automated metadata validation and test execution to improve the reusability of published workflows

BackgroundMany open-source workflow systems have made bioinformatics data analysis procedures portable. Sharing these workflows provides researchers easy access to high-quality analysis methods without the requirement of computational expertise. However, published workflows are not always guaranteed to be reliably reusable. Therefore, a system is needed to lower the cost of sharing workflows in a reusable form. ResultsWe introduce Yevis, a system to build a workflow registry that automatically validates and tests workflows to be published. The validation and test are based on the requirements we defined for a workflow being reusable with confidence. Yevis runs on GitHub and Zenodo and allows workflow hosting without the need of dedicated computing resources. A Yevis registry accepts workflow registration via a GitHub pull request, followed by an automatic validation and test process for the submitted workflow. As a proof of concept, we built a registry using Yevis to host workflows from a community to demonstrate how a workflow can be shared while fulfilling the defined requirements. ConclusionsYevis helps in the building of a workflow registry to share reusable workflows without requiring extensive human resources. By following Yeviss workflow-sharing procedure, one can operate a registry while satisfying the reusable work-flow criteria. This system is particularly useful to individuals or communities that want to share workflows but lacks the specific technical expertise to build and maintain a workflow registry from scratch.

bioinformatics↗

bioRxiv2019

KPHMMER: Hidden Markov Model generator for detecting KEGG PATHWAY-specific genes.

MotivationReinforcement of HMMER search for secondary metabolism-specific Pfam domains should contribute to discover novel biosynthetic machinery of clinically important natural products.\n\nResultsHere we provide a Python-based command line tool, named as KPHMMER, to extract the Pfam domains that are specific in the user-defined set of pathways in the user-defined set of organisms registered in the KEGG database. KPHMMER outperformed the previous study in detecting secondary metabolism-specific Pfam domain set. Furthermore, it was proven that KPHMMER helps reduce the computational cost compared with the case using the whole Pfam-A HMM file. We believe that KPHMMER is a powerful tool enabling to deal with many other genome-sequenced species for more general purpose.\n\nAvailabilityKPHMMER is implemented as a Python package freely available via the package management system \"pip\" and also at https://github.com/suecharo/KPHMMER\n\nContactmaskot@chemsys.t.u-tokyo.ac.jp

pathology↗

bioRxiv2018

KCF-Convoy: efficient Python package to convert KEGG Chemical Function and Substructure fingerprints

MotivationIn silico methodologies to assess pharmaceutical activity and toxicity are increasingly important in QSAR, and many chemical fingerprints have been developed to tackle this problem. Among them, KEGG Chemical Function and Substructure (KCF-S) has been shown to perform well in some pharmaceutical and metabolic studies. However, the software that generates KCF-S fingerprints has limited usability: the input file must be Molfile or SDF format, and the output is only a text file.\n\nResultsWe established a new Python package, KCF-Convoy, to generate KCF format and KCF-S fingerprints from Molfile, SDF, SMILES, and InChI seamlessly. The obtained KCF-S was used in a number of supervised machine-learning methods to distinguish herbicides from other pesticides, and to find characteristic substructures in taxonomy groups.\n\nAvailabilityKCF-Convoy is implemented as a Python package freely available at https://github.com/KCF-Convoy and the user can use the package management system \"pip\" and also the Docker environment.\n\nContactmaskot@chemsys.t.u-tokyo.ac.jp

bioinformatics↗