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Hartmann, T. F.

Publications and source records attributed to Hartmann, T. F..

2 recordsLinked to original sources

mehari: high-performance, strict HGVS-first variant effect prediction

Variant annotation requires the precise and consistent computation of Sequence Ontology (SO) terms and Human Genome Variation Society (HGVS) nomenclature. To ensure robust synchronization between these two key facets, we present mehari, a high-performance variant effect predictor implemented in Rust that employs a strict "HGVS-first" approach. By deterministically projecting variants to transcripts before evaluating functional consequences, mehari structurally aligns HGVS notation and SO terms. Benchmarking on ClinVar demonstrates that mehari achieves exceptional processing speeds and high concordance with established tools like Ensembl VEP, while also providing refined handling for complex biological edge cases such as selenoprotein recoding.

bioinformatics↗

Insane in the vembrane: filtering and transforming VCF/BCF files

Data from sequencing of DNA or RNA samples is routinely scanned for variation. Such variation data is stored in the standardized VCF/BCF format with additional annotations. Analyses of variants usually involve steps where filters are applied to narrow down the list of candidates for further analysis. A number of tools for this task exist, differing in functionality, speed, syntax and supported annotations. Thus, users have to switch between tools depending on the filtering task, and have to adapt to the respective filtering syntax. We present vembrane as a command line VCF/BCF filtering tool that consolidates and extends the filtering functionality of previous software to meet any imaginable filtering use case. To this end, vembrane exposes the VCF/BCF file type specification and its inofficial extensions by the annotation tools VEP and SnpEff as Python data structures. vembrane filter enables filtration by arbitrary Python expressions over (combinations of) annotations, requiring only basic knowledge of the Python programming language. vembrane table allows users to generate tables from subsets of annotations or functions thereof. Finally, it is fast, thanks to pysam, a Python wrapper around htslib, and by relying on Pythons lazy evaluation. Availability and ImplementationSource code and installation instructions are available at github.com/vembrane/vembrane, DOI: 10.5281/zen-odo.7003981.

bioinformatics↗