mqmscanall {qtl} | R Documentation |
Parallelized MQM on multiple phenotypes in a cross object
Description
Parallelized QTL analysis using MQM on multiple phenotypes in a cross object (uses SNOW)
Usage
mqmscanall(cross, multicore=TRUE, n.clusters = 1,batchsize=10,cofactors=NULL, ...)
Arguments
cross |
An object of class |
multicore |
Use multiple cores (only if the package SNOW is available, otherwise this setting will be ignored) |
n.clusters |
Number of parallel processes to spawn, recommended is setting this lower than the number of cores in the computer |
batchsize |
Batch size. The entire set is split in jobs to reduce memory load per core. Each job contains batchsize number of traits per job. |
cofactors |
cofactors, only used when scanfunction is mqmscan.
List of cofactors to be analysed in the QTL model. To set cofactors use |
.
... |
Parameters passed through to the |
Details
Uses mqmscan
to scan for QTL's for each phenotype in the cross object.
It is recomended that the package SNOW is installed before using this function
on large numbers of phenotypes.
Value
Returns a MQMmulti object. This object is a list of scanone
objects that can be plotted using plot.scanone(result[[trait]])
or using mqmplot.multitrait(result)
Author(s)
Ritsert C Jansen; Danny Arends; Pjotr Prins; Karl W Broman broman@wisc.edu
References
Rossini, A., Tierney, L., and Li, N. (2003), Simple parallel statistical computing. R. UW Biostatistics working paper series University of Washington. 193
Tierney, L., Rossini, A., Li, N., and Sevcikova, H. (2004), The snow Package: Simple Network of Workstations. Version 0.2-1.
See Also
The MQM tutorial: https://rqtl.org/tutorials/MQM-tour.pdf
-
MQM
- MQM description and references -
mqmscan
- Main MQM single trait analysis -
mqmscanall
- Parallellized traits analysis -
mqmaugment
- Augmentation routine for estimating missing data -
mqmautocofactors
- Set cofactors using marker density -
mqmsetcofactors
- Set cofactors at fixed locations -
mqmpermutation
- Estimate significance levels -
scanone
- Single QTL scanning
Examples
#Doing a multitrait analysis
data(multitrait)
multitrait <- calc.genoprob(multitrait)
cof <- mqmsetcofactors(multitrait,3)
multitrait <- fill.geno(multitrait)
result <- mqmscanall(multitrait,cofactors=cof,batchsize=5)
mqmplot.multitrait(result,"lines")