SUMMARY: We present Alignoth, a lightweight command line application that generates self-contained portable HTML reports of DNA sequencing read alignment pileups and additionally supports export to static formats such as PNG, SVG, and PDF as well as a JSON based embeddable representation. The HTML reports feature read name search and mapping-quality-based read highlighting, and require only minimal storage, making them practical to share, inspect, or integrate into broader reporting systems. They can be created in headless (i.e. terminal only) environments while being interactively inspected afterwards. AVAILABILITY AND IMPLEMENTATION: Alignoth is freely available under the MIT license at https://github.com/alignoth/alignoth (doi: https://doi.org/10.5281/zenodo.15837719). It is implemented in Rust and can be installed via Cargo or Conda.

BACKGROUND: Existing tools for virus variant identification can pinpoint the most abundant virus variant in a sequencing sample. However, patients can be infected by more than one variant of the same virus species or strain, for example by multiple variants of SARS-CoV-2. This leads to the more complicated problem of virus variant quantification from samples containing virus mixtures. RESULTS: We report on improvements of Orthanq, our generic tool for haplotype quantification, and show how it can be applied to perform uncertainty aware quantification of virus variants. We evaluate this ability on simulated and real SARS-CoV-2 and HIV-1 virus mixture datasets and show that Orthanq outperforms other state of the art approaches. CONCLUSIONS: Orthanq performs identification and uncertainty-aware quantification of known virus variants of any virus species, in particular also in samples with mixed infections. With extensive built-in visualizations and reporting of alternative solutions with posterior densities, users can easily evaluate the uncertainty of the results.

Private Information Retrieval (PIR) allows a client to request entries from a public database held by k servers without revealing any information about the requested data to the servers. PIR is classified into two classes: (i) Multi-server PIR protocols where the request is split among k≥2 non-colluding servers, and Single-server PIR protocols where exactly k=1 server holds the database while the query is protected via certain computational hardness assumptions.