title: Computational and statistical approaches to analyzing variants identified by exome sequencing.
abstract: New sequencing technology has enabled the identification of thousands of single nucleotide polymorphisms in the exome, and many computational and statistical approaches to identify disease-association signals have emerged.
authors.affiliation: Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA.
authors.forename: Nathan O
authors.initials: NO
authors.lastname: Stitziel
authors.forename: Adam
authors.initials: A
authors.lastname: Kiezun
authors.forename: Shamil
authors.initials: S
authors.lastname: Sunyaev
mesh_terms: D000483:Alleles; D019295:Computational Biology; D003627:Data Interpretation, Statistical; D059472:Exome; D005787:Gene Frequency; D030342:Genetic Diseases, Inborn / Q000175:diagnosis / Q000235:genetics; D056426:Genetic Loci; D020022:Genetic Predisposition to Disease; D005828:Genetics, Population / Q000379:methods*; D015894:Genome, Human; D023281:Genomics / Q000379:methods*; D006801:Humans; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D017422:Sequence Analysis, DNA