Publication | Open Access
Interpreting <i>de novo</i> Variation in Human Disease Using denovolyzeR
127
Citations
10
References
2015
Year
GeneticsGenetic EpidemiologyDisease Gene IdentificationGenomicsComputational GenomicsBiostatisticsPublic HealthMolecular DiagnosticsVariant InterpretationPersonal GenomicsGenetic VariantsRobust Statistical EvaluationHuman DiseaseStatistical GeneticsFunctional GenomicsBioinformaticsNext-generation SequencingComputational BiologySystems BiologyMedicine
Spontaneously arising (de novo) genetic variants are important in human disease, yet every individual carries many such variants, with a median of 1 de novo variant affecting the protein-coding portion of the genome. A recently described mutational model provides a powerful framework for the robust statistical evaluation of such coding variants, enabling the interpretation of de novo variation in human disease. Here we describe a new open-source software package, denovolyzeR, that implements this model and provides tools for the analysis of de novo coding sequence variants.
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