ArticleBioinformatics (Oxford, England)2024
HAT: de novo variant calling for highly accurate short-read and long-read sequencing data.
Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- TriosCompass: a snakemake workflow for integrated detection of SNVs, indels, STRs, and structural de novo variants in parent-child trios.Bioinformatics (Oxford, England) · 2026Article
- Variant-resolved prediction of context-specific isoform variation with a graph-based attention model.Cell genomics · 2026Article
- Whole Genome Sequencing Reveals amedRxiv : the preprint server for health sciences · 2026Article
- Long-read sequencing of families reveals increased germline and postzygotic mutation rates in repetitive DNA.Nature communications · 2026Article
- Whole-genome sequencing reveals individual and cohort level insights into chromosome 9p syndromes.Genome medicine · 2025Article
- Decomposition of phenotypic heterogeneity in autism reveals underlying genetic programs.Nature genetics · 2025Article
- Efficient identification of de novo mutations in family trios: a consensus-based informatic approach.Life science alliance · 2025Article
- Acorn: an R package for de novo variant analysis.BMC bioinformatics · 2023Article
Corrections and comments
- Update ofHAT:2023
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
motivationde novo variants (DNVs) are variants that are present in offspring but not in their parents. DNVs are both important for examining mutation rates as well as in the identification of disease-related variation. While efforts have been made to call DNVs, calling of DNVs is still challenging from parent-child sequenced trio data. We developed Hare And Tortoise (HAT) as an automated DNV detection workflow for highly accurate short-read and long-read sequencing data. Reliable detection of DNVs is important for human genomics and HAT addresses this need.
resultsHAT is a computational workflow that begins with aligned read data (i.e. CRAM or BAM) from a parent-child sequenced trio and outputs DNVs. HAT detects high-quality DNVs from Illumina short-read whole-exome sequencing, Illumina short-read whole-genome sequencing, and highly accurate PacBio HiFi long-read whole-genome sequencing data. The quality of these DNVs is high based on a series of quality metrics including number of DNVs per individual, percent of DNVs at CpG sites, and percent of DNVs phased to the paternal chromosome of origin. AVAILABILITY AND IMPLEMENTATION: https://github.com/TNTurnerLab/HAT.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.