MOTIVATION: Changes in genome organisation contribute to genetic disease when they disrupt gene function or regulation. Structural rearrangements may interrupt coding sequence or alter expression through promoter loss or gain, chromatin changes, copy-number variation, or disruption of short-range regulatory elements. Although short-read sequencing excels at detecting small variants, it performs poorly at resolving breakpoints of large rearrangements, especially in repetitive or low-complexity regions. Long-read sequencing overcomes these limitations, but analytical tools have not kept pace, making accurate identification and annotation of large structural variants challenging. RESULTS: We developed AgileStructure, a desktop application for locating and annotating large‑scale genomic rearrangements using aligned long‑read data. The software enables user‑guided exploration of breakpoint‑spanning reads, supporting accurate interpretation of complex events and filling a key gap in current structural variant analysis workflows. AVAILABILITY AND IMPLEMENTATION: Source code, binaries, user guide, and example aligned read data, are available on GitHub: https://github.com/msjimc/AgileStructure. An archived version is also available on Zenodo at https://doi.org/10.5281/zenodo.18610110.

SUMMARY: Mitochondrial DNA sequences are used extensively in phylogeographic and phylogenetic studies for a wide range of organisms. With the advent of low-cost, high throughput 'next generation' DNA sequencing, and user-friendly bioinformatics pipelines for generating and annotating whole mitochondrial genome assemblies, the analysis of whole mitochondrial genomes has become an important component of phylogenomic studies for taxa with high species diversity but limited coverage for other genomic resources. An important step in characterizing de novo mitochondrial genome assemblies is to evaluate and describe structural rearrangements relative to reference taxa. Accessible tools are needed to help visualize gene and noncoding feature complement, their order and strand orientation. However, there are few dedicated applications that generate high quality genome diagrams. Here we present circularMT and circularMT-console that allow users to create highly customizable, publication quality images, of linear and circular mitochondrial genome maps, either individually, or integrated into an analysis pipeline. AVAILABILITY AND IMPLEMENTATION: Both applications are implemented in C#, with binaries, source code and user guides available on GitHub (https://github.com/msjimc/circularMT). An archive of the published version is available on Zenodo (https://zenodo.org/records/10912319). SUPPLEMENTARY INFORMATION: This paper has no supplementary data.

MOTIVATION: In attempts to determine the genetic causes of human disease, researchers are often faced with a large number of candidate genes. Linkage studies can point to a genomic region containing hundreds of genes, while the high-throughput sequencing approach will often identify a great number of non-synonymous genetic variants. Since systematic experimental verification of each such candidate gene is not feasible, a method is needed to decide which genes are worth investigating further. Computational gene prioritization presents itself as a solution to this problem, systematically analyzing and sorting each gene from the most to least likely to be the disease-causing gene, in a fraction of the time it would take a researcher to perform such queries manually. RESULTS: Here, we present Gene TIssue Expression Ranker (GeneTIER), a new web-based application for candidate gene prioritization. GeneTIER replaces knowledge-based inference traditionally used in candidate disease gene prioritization applications with experimental data from tissue-specific gene expression datasets and thus largely overcomes the bias toward the better characterized genes/diseases that commonly afflict other methods. We show that our approach is capable of accurate candidate gene prioritization and illustrate its strengths and weaknesses using case study examples. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://dna.leeds.ac.uk/GeneTIER/. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Exome sequencing has become a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying disease-causing mutations among thousands of candidate variants remains a non-trivial task. RESULTS: Here we describe a new variant prioritization tool, OVA (ontology variant analysis), in which user-provided phenotypic information is exploited to infer deeper biological context. OVA combines a knowledge-based approach with a variant-filtering framework. It reduces the number of candidate variants by considering genotype and predicted effect on protein sequence, and scores the remainder on biological relevance to the query phenotype.We take advantage of several ontologies in order to bridge knowledge across multiple biomedical domains and facilitate computational analysis of annotations pertaining to genes, diseases, phenotypes, tissues and pathways. In this way, OVA combines information regarding molecular and physical phenotypes and integrates both human and model organism data to effectively prioritize variants. By assessing performance on both known and novel disease mutations, we show that OVA performs biologically meaningful candidate variant prioritization and can be more accurate than another recently published candidate variant prioritization tool. AVAILABILITY AND IMPLEMENTATION: OVA is freely accessible at http://dna2.leeds.ac.uk:8080/OVA/index.jsp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: [email protected].

MOTIVATION: Determination of the relative copy number of single-nucleotide sequence variants (SNVs) within a DNA sample is a frequent experimental goal. Various methods can be applied to this problem, although hybridization-based approaches tend to suffer from high-setup cost and poor adaptability, while others (such as pyrosequencing) may not be accessible to all laboratories. The potential to extract relative copy number information from standard dye-terminator electropherograms has been little explored, yet this technology is cheap and widely accessible. Since several biologically important loci have paralogous copies that interfere with genotyping, and which may also display copy number variation (CNV), there are many situations in which determination of the relative copy number of SNVs is desirable. RESULTS: We have developed a desktop application, QSVanalyzer, which allows high-throughput quantification of the proportions of DNA sequences containing SNVs. In reconstruction experiments, QSVanalyzer accurately estimated the known relative proportions of SNVs. By analyzing a large panel of genomic DNA samples, we demonstrate the ability of the software to analyze not only common biallelic SNVs, but also SNVs within a locus at which gene conversion between four genomic paralogs operates, and within another that is subject to CNV. AVAILABILITY AND IMPLEMENTATION: QSVanalyzer is freely available at http://dna.leeds.ac.uk/qsv/. It requires the Microsoft .NET framework version 2.0, which can be installed on all Microsoft operating systems from Windows 98 onwards. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.