Description Usage Arguments Value Author(s) See Also Examples
Textual and graphical display of linkage disequilibrium (LD) objects
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | ## S3 method for class 'LD'
print(x, digits = getOption("digits"), ...)
## S3 method for class 'LD.data.frame'
print(x, ...)
## S3 method for class 'data.frame'
summary.LD(object, digits = getOption("digits"),
which = c("D", "D'", "r", "X^2", "P-value", "n", " "),
rowsep, show.all = FALSE, ...)
## S3 method for class 'summary.LD.data.frame'
print(x, digits = getOption("digits"), ...)
## S3 method for class 'LD.data.frame'
plot(x,digits=3, colorcut=c(0,0.01, 0.025, 0.5, 0.1, 1),
colors=heat.colors(length(colorcut)), textcol="black",
marker, which="D'", distance, ...)
LDtable(x, colorcut=c(0,0.01, 0.025, 0.5, 0.1, 1),
colors=heat.colors(length(colorcut)), textcol="black",
digits=3, show.all=FALSE, which=c("D", "D'", "r", "X^2",
"P-value", "n"), colorize="P-value", cex, ...)
LDplot(x, digits=3, marker, distance, which=c("D", "D'", "r", "X^2",
"P-value", "n", " "), ... )
|
x,object |
LD or LD.data.frame object |
digits |
Number of significant digits to display |
which |
Name(s) of LD information items to be displayed |
rowsep |
Separator between rows of data, use |
colorcut |
P-value cutoffs points for colorizing LDtable |
colors |
Colors for each P-value cutoff given in |
textcol |
Color for text labels for LDtable |
marker |
Marker used as 'comparator' on LDplot. If omitted separate lines for each marker will be displayed |
distance |
Marker location, used for locating of markers on LDplot. |
show.all |
If TRUE, show all rows/columns of matrix. Otherwise omit completely blank rows/columns. |
colorize |
LD parameter used for determining table cell colors |
cex |
Scaling factor for table text. If absent, text will be scaled to fit within the table cells. |
... |
Optional arguments ( |
None.
Gregory R. Warnes greg@warnes.net
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | g1 <- genotype( c('T/A', NA, 'T/T', NA, 'T/A', NA, 'T/T', 'T/A',
'T/T', 'T/T', 'T/A', 'A/A', 'T/T', 'T/A', 'T/A', 'T/T',
NA, 'T/A', 'T/A', NA) )
g2 <- genotype( c('C/A', 'C/A', 'C/C', 'C/A', 'C/C', 'C/A', 'C/A', 'C/A',
'C/A', 'C/C', 'C/A', 'A/A', 'C/A', 'A/A', 'C/A', 'C/C',
'C/A', 'C/A', 'C/A', 'A/A') )
g3 <- genotype( c('T/A', 'T/A', 'T/T', 'T/A', 'T/T', 'T/A', 'T/A', 'T/A',
'T/A', 'T/T', 'T/A', 'T/T', 'T/A', 'T/A', 'T/A', 'T/T',
'T/A', 'T/A', 'T/A', 'T/T') )
data <- makeGenotypes(data.frame(g1,g2,g3))
# Compute & display LD for one marker pair
ld <- LD(g1,g2)
print(ld)
# Compute LD table for all 3 genotypes
ldt <- LD(data)
# display the results
print(ldt) # textual display
LDtable(ldt) # graphical color-coded table
LDplot(ldt, distance=c(124, 834, 927)) # LD plot vs distance
# more markers makes prettier plots!
data <- list()
nobs <- 1000
ngene <- 20
s <- seq(0,1,length=ngene)
a1 <- a2 <- matrix("", nrow=nobs, ncol=ngene)
for(i in 1:length(s) )
{
rallele <- function(p) sample( c("A","T"), 1, p=c(p, 1-p))
if(i==1)
{
a1[,i] <- sample( c("A","T"), 1000, p=c(0.5,0.5), replace=TRUE)
a2[,i] <- sample( c("A","T"), 1000, p=c(0.5,0.5), replace=TRUE)
}
else
{
p1 <- pmax( pmin( 0.25 + s[i] * as.numeric(a1[,i-1]=="A"),1 ), 0 )
p2 <- pmax( pmin( 0.25 + s[i] * as.numeric(a2[,i-1]=="A"),1 ), 0 )
a1[,i] <- sapply(p1, rallele )
a2[,i] <- sapply(p2, rallele )
}
data[[paste("G",i,sep="")]] <- genotype(a1[,i],a2[,i])
}
data <- data.frame(data)
data <- makeGenotypes(data)
ldt <- LD(data)
plot(ldt, digits=2, marker=19) # do LDtable & LDplot on in a single
# graphics window
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