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README.md

MiMMAl

Using two-component Gaussian mixture modelling to estimate the major allele distribution in genotying data.

Installation

Using R >= 3.3.2, MiMMAl depends on the following packages:

  • ComplexHeatmap (>= 1.12.0)
  • circlize (>= 0.3.10)
  • cowplot (>= 0.7.0)
  • ggplot2 (>= 2.2.1)
  • grid (>= 3.3.2)
  • mixtools (version 1.0.4)

Once those packages have been installed. MiMMAl can be downloaded and installed in the following way.

install.packages("MiMMAl", repos = NULL, type="source")

Running

To run MiMMAl a tab-separated text file needs to be produces containing four columns containing; chromosome (chr), position (pos), raw BAF value (BAF) and the mean/median mirrored BAF of the segment of which the loci belongs (BAFseg), for heterozygous SNPs only.

The minimum requirements for running MiMMAl (runMiMMAl) are to include the samplename, this will be appended to .BAFphased.txt, the output of MiMMAl, that will be produced in the current working directory. You will also have to provide the path and name of the input text file as inputfile.

By default MiMMAl will produce plots representing the fits produced, including the results of the initial search of fits using expectation maximisation to search for a range for sd, as well as the global and local searches of parameter space including means and sd in the current working directory. This can be disabled in the options for MiMMAl.

Testing

One can make some next generation sequencing style input data using the following lines of code in R.

n = 100000

coverage = rpois(n, lambda = 120)

majcov = rbinom(n, size = coverage, prob = 0.6)

majoraf = majcov / coverage

baf = ifelse(runif(n) > 0.5, 1 - majoraf, majoraf)

Additional parameters

There are some additional parameters that can be set in runMiMMAl as required:

  • min.snps refers to the minimum number of SNPs required in a segment for initial mixture modelling when searching for a sd range. Smaller segments are effectively controlled for size by the Kolmogorov-Smirnov test for latter fitting. It is best practice to ensure your segments have supporting loci. Default: 10.
  • sd.width is the fraction of which the range of sd is set either side of the maxima of kernel density smoothing of the initial fits of mixture modelling using expectation maximisation. Default: 1/3.
  • preset.sd if this value is defined, the initial fit will not take place and a range either side of this value as defined by sd.width will be used for the global search. Default: NULL.
  • seed the seed can be set to allow for reproducibility. Default: 1.
  • baf.res or BAF resolution defines the number of intervals in the BAF values. This is defined as 10^-baf.res. Therefore baf.res=2 produces intervals of 0.01 between 0 and 0.5 in the global search for BAF mean. Increasing this increases the number of combinations searched and will increase computational time exponentially. The subsequent local search increases the resolution of the fit further, so MiMMAl will always fit each segment to a higher resolution than this initial global search. Default: 2.
  • use.ks.gate refers to performing a Kolmogorov-Smirnov test prior to mixture modelling a segment. Default: TRUE.

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Using two-component Gaussian mixture modelling to estimate the major allele distribution in genotying data.

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