Computational and statistical approaches to analyzing variants identified by exome sequencing

Nathan O Stitziel; Adam Kiezun; Shamil Sunyaev

doi:10.1186/gb-2011-12-9-227

Computational and statistical approaches to analyzing variants identified by exome sequencing

Genome Biol. 2011 Sep 14;12(9):227. doi: 10.1186/gb-2011-12-9-227.

Authors

Nathan O Stitziel¹, Adam Kiezun, Shamil Sunyaev

Affiliation

¹ Division of Cardiovascular Medicine, Brigham and Women’s Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA.

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.

Publication types

Research Support, N.I.H., Extramural
Review

MeSH terms

Alleles
Computational Biology*
Data Interpretation, Statistical
Exome*
Gene Frequency
Genetic Diseases, Inborn / diagnosis
Genetic Diseases, Inborn / genetics
Genetic Loci
Genetic Predisposition to Disease
Genetics, Population / methods*
Genome, Human
Genomics / methods*
Humans
Phenotype
Polymorphism, Single Nucleotide
Sequence Analysis, DNA

Abstract

Publication types

MeSH terms

Grants and funding