title: Phen-Gen: combining phenotype and genotype to analyze rare disorders.
abstract: We introduce Phen-Gen, a method that combines patients' disease symptoms and sequencing data with prior domain knowledge to identify the causative genes for rare disorders. Simulations revealed that the causal variant was ranked first in 88% of cases when it was a coding variant-a 52% advantage over a genotype-only approach-and Phen-Gen outperformed other existing prediction methods by 13-58%. If disease etiology was unknown, the causal variant was assigned the top rank in 71% of simulations. Phen-Gen is available at http://phen-gen.org/.
authors.affiliation: Computational and Systems Biology Group, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore.
authors.forename: Asif
authors.initials: A
authors.lastname: Javed
authors.affiliation: Computational and Systems Biology Group, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore.
authors.forename: Saloni
authors.initials: S
authors.lastname: Agrawal
authors.affiliation: Computational and Systems Biology Group, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore.
authors.forename: Pauline C
authors.initials: PC
authors.lastname: Ng
mesh_terms: D002874:Chromosome Mapping / Q000379:methods*; D057225:Data Mining / Q000379:methods; D030541:Databases, Genetic; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D005820:Genetic Testing / Q000379:methods*; D015894:Genome, Human / Q000235:genetics*; D005838:Genotype; D006801:Humans; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D035583:Rare Diseases / Q000175:diagnosis* / Q000235:genetics*; D012984:Software
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