bqtl1.0-36 package

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