parallel_apply

Separate a matrix in a list of matrices of length the number of cores and
apply a function on the columns in parallel

Linkage disequilibrium visualizations of up to several hundreds of single nucleotide polymorphisms (SNPs), annotated with chromosomic positions and gene names. Two types of plots are available for small numbers of SNPs (<40) and for large numbers (tested up to 500). Both can be extended by combining other ggplots, e.g. association studies results, and functions enable to directly visualize the effect of SNP selection methods, as minor allele frequency filtering and TagSNP selection, with a second correlation heatmap. The SNPs correlations are computed on Genotype Data objects from the 'GWASTools' package using the 'SNPRelate' package, and the plots are customizable 'ggplot2' and 'gtable' objects and are annotated using the 'biomaRt' package. Usage is detailed in the vignette with example data and results from up to 500 SNPs of 1,200 scans are in Charlon T. (2019) <doi:10.13097/archive-ouverte/unige:161795>.

Thomas Charlon

snplinkage

Single Nucleotide Polymorphisms Linkage Disequilibrium
Visualizations

Karl Forner

Alessandro Di Cara

Jérôme Wojcik

parallel_apply function

<dl><dt>m_data</dt>
<dd>Data matrix</dd>
<dt>apply_fun</dt>
<dd>Function to apply</dd>
<dt>n_cores</dt>
<dd>Number of cores</dd>
<dt>...</dt>
<dd>Passed to apply_fun</dd></dl>

Arguments

Separate a matrix in a list of matrices of length the number of cores and
apply a function on the columns in parallel — parallel_apply

<dl>

<dt>m_data</dt>
<dd>Data matrix</dd>


<dt>apply_fun</dt>
<dd>Function to apply</dd>


<dt>n_cores</dt>
<dd>Number of cores</dd>


<dt>...</dt>
<dd>Passed to apply_fun</dd>

</dl>

parallel_apply: Separate a matrix in a list of matrices of length the number of cores and apply a function on the columns in parallel

Description

Usage

Value

Arguments