estimateFounderEffect: Estimate founder QTL effect

In tavareshugo/MagicHelpR: QTL mapping in Arabidopsis MAGIC lines

Description

This function estimates the phenotypic effect of each accession's allele at a particular marker. It is based on the probabilistic assignment of each MAGIC line to a single accession. The procedure is repeated several times to produce an average estimate and associated uncertainty. This function is based on the function imputed.one.way.anova() from the scripts available at http://mtweb.cs.ucl.ac.uk/mus/www/magic/

Usage

estimateFounderEffect(x, phenotype, marker, n_samples = 500,
  summarised = TRUE, standardised = TRUE, covariates = NULL)

## S4 method for signature 'MagicGenPhen'
estimateFounderEffect(x, phenotype, marker,
  n_samples = 500, summarised = TRUE, standardised = TRUE,
  covariates = NULL)

Arguments

x	an object of class MagicData.
phenotype	the phenotype to get the results from.
marker	the SNP marker to estimate the effects for.
n_samples	number of Monte Carlo samples to draw.
summarised	whether or not to report summarised results. The summarised output gives the mean, median and 2.5 imputations. The two percentiles define the 95 can be used as a confidence interval to report accuracy of the estimates. Default: TRUE
standardised	whether or not the phenotypic values should be standardised to the mean. In that case the result reflects how many standard deviations the estimated effect deviates from the observed trait mean. Default: TRUE
covariates	optional name of column(s) from phenotypes to use as covariate(s). The effect will be estimated from the residuals of a standard linear model between the trait of interest and the specified covariates. Default: NULL

Value

a data.frame with imputed phenotypes for each founder accession.

Examples

## Not run: 
estimateFounderEffect(magic_genotypes, "MN1_29291")

## End(Not run)

tavareshugo/MagicHelpR documentation built on May 4, 2020, 3:01 p.m.