runMiMMAl: The main MiMMAl function.

In georgecresswell/MiMMAl: Using two-component Gaussian mixture modelling to estimate the major allele distribution in genotying data.

Description

This function takes segmented BAF data as input and models the major and minor allele distributions.

Usage

runMiMMAl(samplename, inputfile, min.snps = 10, sd.width = 1/3,
  preset.sd = NULL, seed = 1, baf.res = 2, use.ks.gate = TRUE,
  plot.sd.den = TRUE, plot.lit.plot = TRUE, plot.star.plot = TRUE,
  plot.transformed = TRUE)

Arguments

samplename	The output name for your sample.
inputfile	The file to be read in as containing the columns; chr, pos, BAF, BAFseg.
min.snps	Minimum number of SNPs to model. Default = 10.
sd.width	This value is multiplied by the chosen sd and the tested sd range is determined as the sd±sd.width. Default = 1/3.
preset.sd	Add a float value for the standard deviation if it is to be preset, without this it 'learns' the sd. Default = NULL.
seed	Seed set for reproducibility. Default = 1.
baf.res	10^-baf.res is used as the size of the steps used in the grid search for testing BAF values. Default = 2.
use.ks.gate	Require the data to pass a normality test before modelling. Default = TRUE.
plot.sd.den	Plot the sd density plot? Default = TRUE.
plot.lit.plot	Plot the global grid search? Default = TRUE.
plot.star.plot	Plot the local grid search? Default = TRUE.
plot.transformed	Plot the transformed data? Default = TRUE.

Examples

runMiMMAl()

georgecresswell/MiMMAl documentation built on Oct. 25, 2020, 2:40 p.m.