Bayesian QTL Mapping Toolkit
Some Introductory Comments
Use Laplace Approximations to improve linear approximations to the pos...
Internal BQTL functions
Bayesian QTL Model Fitting
Extract Coefficients from fitted objects
Lookup loci or effects for genetic model formulas
Treat locus as covariate
Extract formula from bqtl object
Approximate marginal posterior for chosen model
Bayesian QTL mapping via Linearized Likelihood
Simulated Marker Data
Simulated Phenotype Data
Marker Map Description for Simulated Data
Simulated Marker Data
Simulated Phenotype Data
Lookup loci or effects for genetic model formulas
Extract loglikelihood, log posterior, or posterior from fitted models
Set up data for QTL mapping
Keep track of fully informative markers or states
Provide a default prior
Create marker map specifications
Translate a marker.frame.object to numeric matrix
Create regressors using expected marker values
Create state.matrix.object
Create moment matrices
Look up numerical index(es) of map locations
Report map location
Look up names of markers or loci
Map Positions Between Markers
Define marker level codes
plots by chromosome location
fitted values from QTL models
Residuals or Predicted Values for linear.bayes objects
Residuals from QTL models
Summarize Laplace approximations
Summarize bqtl object
Summary methods for basic data objects
Summarize Gibbs samples for a k-gene model
MCMC sampling of multigene models
Sample BC1 or Recombinant Inbred loci via approximate posterior.
Sample F2 loci via approximate posterior
One and Two Gene Models Using Linearized Posterior
One and Two Gene Models Using Linearized Posterior
Get loglikelihoods for many models of a common form
Create moment matrices
QTL mapping toolkit for inbred crosses and recombinant inbred lines. Includes maximum likelihood and Bayesian tools.