relationship_plot {GALLO} | R Documentation |
Plot relationship between data and grouping factors
Description
Takes the output from find_genes_qtls_around_markers function and creates a chord plot with the relationship between groups
Usage
relationship_plot(
qtl_file,
x,
y,
grid.col = "gray60",
degree = 90,
canvas.xlim = c(-2, 2),
canvas.ylim = c(-2, 2),
cex,
gap
)
Arguments
qtl_file |
The output from find_genes_qtls_around_markers function |
x |
The first grouping factor, to be plotted in the left hand side of the chord plot |
y |
The second grouping factor, to be plotted in the left hand side of the chord plot |
grid.col |
A character with the grid color for the chord plot or a vector with different colors to be used in the grid colors. Note that when a color vector is provided, the length of this vector must be equal the number of sectors in the chord plot |
degree |
A numeric value corresponding to the starting degree from which the circle begins to draw. Note this degree is always reverse-clockwise |
canvas.xlim |
The coordinate for the canvas in the x-axis. By default is c(-1,1) |
canvas.ylim |
The coordinate for the canvas in the y-axis. By default is c(-1,1) |
cex |
The size of the labels to be printed in the plot |
gap |
A numeric value corresponding to the gap between the chord sectors |
Value
A chords relating x and y
Examples
data(QTLmarkers)
data(gffQTLs)
out.qtls<-find_genes_qtls_around_markers(
db_file=gffQTLs, marker_file=QTLmarkers,
method = "qtl", marker = "snp",
interval = 500000, nThreads = 1)
out.enrich<-qtl_enrich(qtl_db=gffQTLs,
qtl_file=out.qtls, qtl_type = "Name",
enrich_type = "chromosome",
chr.subset = NULL, padj = "fdr",nThreads = 1)
out.enrich$ID<-paste(out.enrich$QTL," - ",
"CHR",out.enrich$CHR,sep="")
out.enrich.filtered<-out.enrich[which(out.enrich$adj.pval<0.05),]
out.qtls$ID<-paste(out.qtls$Name," - ",
"CHR",out.qtls$CHR,sep="")
out.enrich.filtered<-out.enrich.filtered[order(out.enrich.filtered$adj.pval),]
out.qtls.filtered<-out.qtls[which(out.qtls$ID%in%out.enrich.filtered$ID[1:10]),]
out.qtls.filtered[which(out.qtls.filtered$Reference==
"Feugang et al. (2010)"), "color_ref"]<-"purple"
out.qtls.filtered[which(out.qtls.filtered$Reference==
"Buzanskas et al. (2017)"),"color_ref"]<-"pink"
color.grid<-c(rep("black",length(unique(out.qtls.filtered$Abbrev))),
unique(out.qtls.filtered$color_ref))
names(color.grid)<-c(unique(out.qtls.filtered$Abbrev),
unique(out.qtls.filtered$Reference))
relationship_plot(qtl_file=out.qtls.filtered,
x="Abbrev", y="Reference",cex=1,gap=5,
degree = 90, canvas.xlim = c(-5, 5),
canvas.ylim = c(-3, 3), grid.col = color.grid)