Description Usage Arguments Value See Also Examples
cLBL
is an MCMC algorithm that generates posterior samples for a dataset containing both case-control and family trio designs. This function
takes standard pedigree format as input. The input does not allow missing observations and subjects with
missing data are removed. The function returns an object containing posterior
samples after the burn-in period.
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data.fam |
The family portion of data. This dataset should consist of "3n" rows and 6+2*p columns,
where n is the number of case-parent trios, and p is the
number of SNPs. The data should be in standard pedigree format, with the
first 6 columns representing the family ID, individual ID, father ID,
mother ID, sex, and affection status. The other 2*p columns are genotype
data in allelic format, with each allele of a SNP taking up one column.
An example can be found in this package under the name |
data.cac |
The case-control portion of data. This dataset should consist of "n" rows and 6+2*p
columns, where n is the number of individuals of the independent cases and controls, and p
is the number of SNPs. The data should be in standard pedigree format, with
the first 6 columns representing the family ID, individual ID, father ID,
mother ID, sex, and affection status. The other 2*p columns are genotype
data in allelic format, with each allele of a SNP taking up one column.
An example can be found in this package under the name |
input.freq |
Optional. Specify frequency distribution of haplotypes. If not provided, the algorithm will use the estimated frequencies. |
baseline |
Haplotype to be used for baseline coding; default is the most frequent haplotype according to the initial haplotype frequency estimates. This argument should be a character, starting with an h and followed by the baseline haplotype. |
a |
First hyperparameter of the prior for regression coefficients, β. The prior variance of β is 2/λ^2 and λ has Gamma(a,b) prior. The Gamma prior parameters a and b are formulated such that the mean and variance of the Gamma distribution are a/b and a/b^2. The default value of a is 15. |
b |
Second hyperparameter of the Gamma(a,b) distribution described above; default is 15. |
start.beta |
Starting value of all regression coefficients, β; default is 0.01. |
lambda |
Starting value of the λ parameter described above; default is 1. |
D |
Starting value of the D parameter, which is the within-population inbreeding coefficient; default is 0. |
seed |
Seed to be used for the MCMC in Bayesian Lasso; default is a random seed. If exact same results need to be reproduced, seed should be fixed to the same number. |
burn.in |
Burn-in period of the MCMC sampling scheme; default is 10000. |
num.it |
Total number of MCMC iterations including burn-in; default is 40000. |
summary |
Logical. If TRUE, cLBL will return a summary of the analysis. If FALSE, cLBL will return the posterior samples of MCMC. Default is set to be TRUE. |
e |
A (small) number ε in the null hypothesis of no association,
H_0: |β| ≤ ε. The default is 0.1. Changing e from the default of 0.1 may necessitate choosing a
different threshold for Bayes Factor (one of the outputs) to infer
association. Only used if |
ci.level |
Credible probability. The probability that the true value of β will
be within the credible interval. Default is 0.95, which corresponds to a 95% posterior credible interval. Only used if |
If summary = FALSE
, return a list with the following components:
The list of haplotypes used in the analysis. The last column is the reference haplotype.
Posterior samples of betas stored in a matrix.
A vector of (num.it-burn.in) posterior samples of lambda.
Posterior samples of the frequencies of haplotypes stored in a matrix format, in the same order as haplotypes.
The haplotype distribution used to initiate the MCMC.
If summary = TRUE
, return the result of LBL_summary.
For details, see the description of the LBL_summary
function.
LBL
, famLBL
, LBL_summary
, print_LBL_summary
, LBL-package
.
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