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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. © 2012 Sifrim et al.; licensee BioMed Central Ltd.
Sifrim, A., Van Houdt, J. K. J., Tranchevent, L. C., Nowakowska, B., Sakai, R., Pavlopoulos, G. A., … Aerts, J. (2012). Annotate-it: A Swiss-knife approach to annotation, analysis and interpretation of single nucleotide variation in human disease. Genome Medicine, 4(9). https://doi.org/10.1186/gm374