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HAT: de novo variant calling for highly accurate short-read and long-read sequencing data
MOTIVATION: de novo variant (DNV) calling is challenging from parent-child sequenced trio data. We developed Hare And Tortoise (HAT) to work as an automated workflow to detect DNVs in highly accurate short-read and long-read sequencing data. Reliable detection of DNVs is important for human genetics...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900919/ https://www.ncbi.nlm.nih.gov/pubmed/36747667 http://dx.doi.org/10.1101/2023.01.27.525940 |
Sumario: | MOTIVATION: de novo variant (DNV) calling is challenging from parent-child sequenced trio data. We developed Hare And Tortoise (HAT) to work as an automated workflow to detect DNVs in highly accurate short-read and long-read sequencing data. Reliable detection of DNVs is important for human genetics studies (e.g., autism, epilepsy). RESULTS: HAT is a workflow to detect DNVs from short-read and long read sequencing data. This workflow 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 short-read whole-exome sequencing, short-read whole-genome sequencing, and highly accurate long-read sequencing data. |
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