genoClusterPlot {GWASTools} | R Documentation |
Generates either X,Y or R,Theta cluster plots for specified SNP's.
genoClusterPlot(intenData, genoData, plot.type = c("RTheta", "XY"), snpID, main.txt = NULL, by.sex = FALSE, scan.sel = NULL, scan.hilite = NULL, start.axis.at.0 = FALSE, colors = c("default", "neon", "primary"), verbose = TRUE, ...) genoClusterPlotByBatch(intenData, genoData, plot.type = c("RTheta", "XY"), snpID, batchVar, main.txt = NULL, scan.sel = NULL, colors = c("default", "neon", "primary"), verbose = TRUE, ...)
intenData |
|
genoData |
|
plot.type |
The type of plots to generate. Possible values are "RTheta" (default) or "XY". |
snpID |
A numerical vector containing the SNP number for each plot. |
batchVar |
A character string indicating which annotation variable should be used as the batch. |
main.txt |
A character vector containing the title to give to each plot. |
by.sex |
Logical value specifying whether to indicate sex on the
plot. If |
scan.sel |
integer vector of scans to include in the plot. If |
scan.hilite |
integer vector of scans to highlight in the plot
with different colors. If |
start.axis.at.0 |
Logical for whether the min value of each axis should be 0. |
colors |
Color scheme to use for genotypes. "default" is colorblind safe (colorbrewer Set2), "neon" is bright orange/green/fuschia, and "primary" is red/green/blue. |
verbose |
Logical value specifying whether to show progress. |
... |
Other parameters to be passed directly to |
Either 'RTheta' (default) or 'XY' plots can be generated. R and Theta
values are computed from X and Y using the formulas r <- x+y
and
theta <- atan(y/x)*(2/pi)
.
If by.sex==TRUE
, females are indicated with circles and males
with crosses.
Caitlin McHugh
# create data object library(GWASdata) data(illuminaScanADF, illuminaSnpADF) xyfile <- system.file("extdata", "illumina_qxy.gds", package="GWASdata") xy <- GdsIntensityReader(xyfile) xyData <- IntensityData(xy, scanAnnot=illuminaScanADF, snpAnnot=illuminaSnpADF) genofile <- system.file("extdata", "illumina_geno.gds", package="GWASdata") geno <- GdsGenotypeReader(genofile) genoData <- GenotypeData(geno, scanAnnot=illuminaScanADF, snpAnnot=illuminaSnpADF) # select first 9 snps snpID <- illuminaSnpADF$snpID[1:9] rsID <- illuminaSnpADF$rsID[1:9] par(mfrow=c(3,3)) # plot 3x3 genoClusterPlot(xyData, genoData, snpID=snpID, main.txt=rsID) # select samples scan.sel <- illuminaScanADF$scanID[illuminaScanADF$race == "CEU"] genoClusterPlot(xyData, genoData, snpID=snpID, main.txt=rsID, scan.sel=scan.sel, by.sex=TRUE) genoClusterPlot(xyData, genoData, snpID=snpID, main.txt=rsID, scan.hilite=scan.sel) close(xyData) close(genoData) ## affy data - cluster plots by plate data(affyScanADF, affySnpADF) xyfile <- system.file("extdata", "affy_qxy.nc", package="GWASdata") xy <- NcdfIntensityReader(xyfile) xyData <- IntensityData(xy, scanAnnot=affyScanADF, snpAnnot=affySnpADF) genofile <- system.file("extdata", "affy_geno.nc", package="GWASdata") geno <- NcdfGenotypeReader(genofile) genoData <- GenotypeData(geno, scanAnnot=affyScanADF, snpAnnot=affySnpADF) # select first 9 snps snpID <- affySnpADF$snpID[1:9] rsID <- affySnpADF$rsID[1:9] genoClusterPlotByBatch(xyData, genoData, snpID=snpID, main.txt=rsID, batchVar="plate") close(xyData) close(genoData)