Compute Extended Haplotype Homozygosity (EHH) and integrated EHH (iHH) for a given focal SNPs.
calc_ehh(haplohh, mrk, limhaplo = 2, limehh = 0.05, maxgap=NA, plotehh = TRUE,
lty = 1, lwd = 1.5, col = c("blue", "red"), xlab = "Position",
ylab = expression(Extended ~ haplotype ~ homozygosity ~ (italic(EHH))),
cex.lab = 1.25, main = NA, cex.main = 1.5)
An object of class haplohh
(see data2haplohh
).
Integer representing the number of the focal marker
Minimal number of haplotypes to continue computing EHH away from the core SNP. Useless, if no missing data. However, when some data are missing, haplotypes with missing data are removed from the computation. Hence as we compute EHH further from the core SNP, less haplotypes are expected
Limit below which EHH stops to be evaluated
Maximum allowed gap in bp between two SNPs below which EHH stops to be evaluated (default=NA, i.e., no limitation)
If TRUE, EHH estimates for both the ancestral and derived allele are plotted for each position
Line type for the ancestral and derived allele iHH (respectively) curves
Line width for the ancestral and derived allele iHH (respectively) curves
Color for the ancestral and derived allele iHH (respectively) curves
Legend for the x--axis
Legend for the y--axis
Size of the axis legend
Main legend of the EHHS plot
Size of the main legend
The returned value is a list containing the following components:
A matrix of two rows and nsnps columns containing EHH estimates at each chromosome position relative to the focal SNP for the ancestral (first row) and derived (second row) alleles.
A matrix of two rows and nsnps columns containing the number of evaluated haplotypes at each chromosome position relative to the focal SNP for the ancestral (first row) and derived (second row) alleles.
A vector of two elements corresponding respectively to the iHH (integrated EHH) for the ancestral and derived allele.
EHH are computed at each position upstream and downstream the focal SNP for both the derived and ancestral allele. This allows in turn the computation of the integrated EHH relative to map distances (iHH).
Gautier, M. and Naves, M. (2011). Footprints of selection in the ancestral admixture of a New World Creole cattle breed. Molecular Ecology, 20, 3128--3143.
Sabeti, P.C. et al. (2002). Detecting recent positive selection in the human genome from haplotype structure. Nature, 419, 832--837.
Sabeti, P.C. et al. (2007). Genome-wide detection and characterization of positive selection in human populations. Nature, 449, 913--918.
Tang, K. and Thornton, K.R. and Stoneking, M. (2007). A New Approach for Using Genome Scans to Detect Recent Positive Selection in the Human Genome. Plos Biology, 7, e171.
Voight, B.F. and Kudaravalli, S. and Wen, X. and Pritchard, J.K. (2006). A map of recent positive selection in the human genome. Plos Biology, 4, e72.
calc_ehhs,data2haplohh,scan_hh
# NOT RUN {
#example haplohh object (280 haplotypes, 1424 SNPs)
#see ?haplohh_cgu_bta12 for details
data(haplohh_cgu_bta12)
#computing EHH statisitics for the focal SNP at position 456
# which displays a strong signal of selection
res.ehh<-calc_ehh(haplohh_cgu_bta12,mrk=456)
# }
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