plotLd | R Documentation |
Plots the linkage disequilibrium between pairs of SNPs, as a blue density or black points, with a red loess. Possibility to add two analytical approximations of E[r^2] at equilibrium (see McVean, Handbook of Stat Gen, 2007): 1 / (1 + 4 Ne c x) by Sved (1971) and (10 + 4 Ne c x) / (22 + 13 * 4 Ne c x + (4 Ne c x)^2) by Ohta and Kimura (1971).
plotLd(
x,
y,
main = "",
estim = "r2",
use.density = TRUE,
xlab = "Physical distance (bp)",
ylab = paste0("Linkage disequilibrium (", estim, ")"),
span = 1/10,
degree = 1,
evaluation = 50,
sample.size = NULL,
add.ohta.kimura = FALSE,
add.sved = FALSE,
Ne = NULL,
c = NULL,
xlim
)
x |
vector of distances between SNPs (see |
y |
vector of LD estimates (see |
main |
main title |
estim |
estimator of pairwise LD corresponding to the values in y (r2/r) |
use.density |
if TRUE, uses smoothScatter; otherwise, use scatter.smooth |
xlab |
label for the x axis |
ylab |
label for the y axis |
span |
the parameter alpha which controls the degree of smoothing (see |
degree |
the degree of the polynomials to be used (see |
evaluation |
number of points at which to evaluate the smooth curve (see |
sample.size |
nb of sampled haplotypes, n, used to estimate the pairwise LD; if not NULL, n is used to plot the horizontal line at the r value above which the null hypothesis "D=0" is rejected, where r = D / sqrt(f_A f_a f_B f_b) and X^2 = n r^2 is the test statistic asymptotically following a Chi2(df=1) (see McVean, Handbook of Statistical Genetics, 2007, and Pritchard and Przewoski, AJHG, 2001) |
add.ohta.kimura |
add the analytical approximation by Ohta and Kimura (1971); requires Ne and c |
add.sved |
add the analytical approximation by Sved (1971); requires Ne and c |
Ne |
effective population size |
c |
recomb rate in events per base per generation |
xlim |
numeric vector of length 2 specifying the x-axis limit (optional) |
invisible list
Timothee Flutre
estimLd
, distSnpPairs
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.