@inbook{bac9eb5bd2054268aa3fd863a600aaa3,
title = "R for Genome-Wide Association Studies",
abstract = "In recent years R has become de facto statistical programming language of choice for statisticians and it is also arguably the most widely used generic environment for analysis of high-throughput genomic data. In this chapter we discuss some approaches to improve performance of R when working with large SNP datasets.",
keywords = "Quantitative Genetics (incl Disease and Trait Mapping Genetics)",
author = "Cedric Gondro and Porto-Neto, \{Laercio R\} and Lee, \{S H\}",
year = "2013",
doi = "10.1007/978-1-62703-447-0\_1",
language = "English",
isbn = "9781627034470",
series = "Methods in Molecular Biology",
publisher = "Humana Press",
number = "1019",
pages = "1--17",
editor = "Cedric Gondro and \{van der Werf\}, Julius and Ben Hayes",
booktitle = "Genome-Wide Association Studies and Genomic Predictions",
edition = "1",
}