@inbook{6878cb08a66e4ef0ba26288d0a8e6335,
title = "SCAN: A systems biology approach to pharmacogenomic discovery",
abstract = "Genome-wide association (GWA) studies have identified thousands of genetic variants that contribute to disease and pharmacologic traits. More recently, high-throughput sequencing studies promise to provide a more complete catalog of genetic variants with roles in human phenotypic variation. Yet, characterizing the influence of functional variants on genes, RNAs, proteins, and ultimately disease or pharmacologic traits is a critical challenge for a vast majority of the implicated susceptibility loci. Here we describe SCAN, a bioinformatics resource we have developed to elucidate the functional consequences of genetic variants identified by genome-wide scans. In particular, this public resource implements a systems biology approach to pharmacogenomic discovery.",
keywords = "Expression profiling, Genetic variation, Pharmacogenomics, SNP function, Transcriptome, eQTLs",
author = "Gamazon, {Eric R.} and Huang, {R. Stephanie} and Cox, {Nancy J.}",
year = "2013",
doi = "10.1007/978-1-62703-435-7_14",
language = "English (US)",
isbn = "9781627034340",
series = "Methods in Molecular Biology",
pages = "213--224",
editor = "Federico Innocenti and {van Schaik}, {Ron H.N.}",
booktitle = "Pharmacogenomics",
}