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Showing 1–6 of 6 results
Advanced filters: Author: Donate Weghorn Clear advanced filters

  • MutPanning is a new method to detect cancer driver genes that identifies genes with an excess of mutations in unusual nucleotide contexts. Applying this to whole-exome sequencing data from 11,873 tumor–normal pairs identifies 460 driver genes.

    • Felix Dietlein
    • Donate Weghorn
    • Shamil R. Sunyaev
    Research
    Nature Genetics
    Volume: 52, P: 208-218

  • Cancer driver mutations can occur within noncoding genomic sequences. Here, the authors develop a statistical approach to identify candidate noncoding driver mutations in DNase I hypersensitive sites in breast cancer and experimentally demonstrate they are regulatory elements of known cancer genes.

    • Matteo D′Antonio
    • Donate Weghorn
    • Kelly A Frazer
    ResearchOpen Access
    Nature Communications
    Volume: 8, P: 1-16

  • This study presents a probabilistic framework for inferring negative and positive selection in human cancers that addresses the problem of mutation rate variation. Applying the model to sequencing data from 17 cancer types identifies new significantly mutated genes and detects significant signals of negative selection in many cancer types.

    • Donate Weghorn
    • Shamil Sunyaev
    Research
    Nature Genetics
    Volume: 49, P: 1785-1788

  • Evidence that somatic mutation rates in introns exceed those in exons challenges the molecular evolution tenet that mutation rate and sequence function are independent. Here, authors analyze germline de novo mutations and reveal no evidence for mutation rate differences between exons and introns.

    • Miguel Rodriguez-Galindo
    • Sònia Casillas
    • Antonio Barbadilla
    ResearchOpen Access
    Nature Communications
    Volume: 11, P: 1-9

  • Shamil Sunyaev, David Beier and colleagues report an analysis of the fitness effects of heterozygous protein-truncating variants from the Exome Aggregation Consortium. They find that high heterozygous selection coefficients are enriched in Mendelian disease-associated genes and essential mouse genes, suggesting that this coefficient can be used to prioritize candidate disease-associated genes from clinical exome-sequencing data.

    • Christopher A Cassa
    • Donate Weghorn
    • Shamil R Sunyaev
    Research
    Nature Genetics
    Volume: 49, P: 806-810