relationship_plot: Plot relationship between data and grouping factors

In GALLO: Genomic Annotation in Livestock for Positional Candidate LOci

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)

GALLO documentation built on June 22, 2024, 9:17 a.m.