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• W2167588342 abstract "The increasing size and complexity of exome/genome sequencing data requires new tools for clinical geneticists to discover disease-causing variants. Bottlenecks in identifying the causative variation include poor cross-sample querying, constantly changing functional annotation and not considering existing knowledge concerning the phenotype. We describe a methodology that facilitates exploration of patient sequencing data towards identification of causal variants under different genetic hypotheses. Annotate-it facilitates handling, analysis and interpretation of high-throughput single nucleotide variant data. We demonstrate our strategy using three case studies. Annotate-it is freely available and test data are accessible to all users at http://www.annotate-it.org ." @default.
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• W2167588342 date "2012-01-01" @default.
• W2167588342 modified "2023-09-26" @default.
• W2167588342 title "Annotate-it: a Swiss-knife approach to annotation, analysis and interpretation of single nucleotide variation in human disease" @default.
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• W2167588342 doi "https://doi.org/10.1186/gm374" @default.
• W2167588342 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3580443" @default.
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