Zbeta_BetaCDF {zalpha} | R Documentation |
Runs the Zbeta function using a cumulative beta distribution function on the r-squared values for the region
Description
Returns a Z_{\beta}^{BetaCDF}
value for each SNP location supplied to the function, based on
the expected r^2
values given an LD profile and genetic distances.
For more information about the Z_{\beta}^{BetaCDF}
statistic, please see Jacobs (2016).
The Z_{\beta}^{BetaCDF}
statistic is defined as:
Z_{\beta}^{BetaCDF}=\frac{\sum_{i \in L,j \in R}\frac{B(r^2_{i,j};a,b)}{B(a,b)}}{|L||R|}
where |L|
and |R|
are the number of SNPs to the left and right of the current locus within the given window ws
, r^2
is equal to
the squared correlation between a pair of SNPs, and \frac{B(r^2_{i,j};a,b)}{B(a,b)}
is the cumulative distribution function for the Beta distribution given
the estimated a and b parameters from the LD profile.
Usage
Zbeta_BetaCDF(
pos,
ws,
x,
dist,
LDprofile_bins,
LDprofile_Beta_a,
LDprofile_Beta_b,
minRandL = 4,
minRL = 25,
X = NULL
)
Arguments
pos |
A numeric vector of SNP locations |
ws |
The window size which the |
x |
A matrix of SNP values. Columns represent chromosomes; rows are SNP locations. Hence, the number of rows should equal the length of the |
dist |
A numeric vector of genetic distances (e.g. cM, LDU). This should be the same length as |
LDprofile_bins |
A numeric vector containing the lower bound of the bins used in the LD profile. These should be of equal size. |
LDprofile_Beta_a |
A numeric vector containing the first estimated Beta parameter for the corresponding bin in the LD profile. |
LDprofile_Beta_b |
A numeric vector containing the second estimated Beta parameter for the corresponding bin in the LD profile. |
minRandL |
Minimum number of SNPs in each set R and L for the statistic to be calculated. Default is 4. |
minRL |
Minimum value for the product of the set sizes for R and L. Default is 25. |
X |
Optional. Specify a region of the chromosome to calculate |
Details
The LD profile describes the expected correlation between SNPs at a given genetic distance, generated using simulations or
real data. Care should be taken to utilise an LD profile that is representative of the population in question. The LD
profile should consist of evenly sized bins of distances (for example 0.0001 cM per bin), where the value given is the (inclusive) lower
bound of the bin. Ideally, an LD profile would be generated using data from a null population with no selection, however one can be generated
using this data. See the create_LDprofile
function for more information on how to create an LD profile.
Value
A list containing the SNP positions and the Z_{\beta}^{BetaCDF}
values for those SNPs
References
Jacobs, G.S., T.J. Sluckin, and T. Kivisild, Refining the Use of Linkage Disequilibrium as a Robust Signature of Selective Sweeps. Genetics, 2016. 203(4): p. 1807
See Also
Examples
## load the snps and LDprofile example datasets
data(snps)
data(LDprofile)
## run Zbeta_BetaCDF over all the SNPs with a window size of 3000 bp
Zbeta_BetaCDF(snps$bp_positions,3000,as.matrix(snps[,3:12]),snps$cM_distances,
LDprofile$bin,LDprofile$Beta_a,LDprofile$Beta_b)
## only return results for SNPs between locations 600 and 1500 bp
Zbeta_BetaCDF(snps$bp_positions,3000,as.matrix(snps[,3:12]),snps$cM_distances,
LDprofile$bin,LDprofile$Beta_a,LDprofile$Beta_b,X=c(600,1500))