Given a set of genotype counts, mtest examines a large number of possible outcomes with the same set of allele counts. For each table, it computes four test statistics and compares them with the observed values. It returns the total probability of all tables with test statistics as “extreme” or more so than the observed. It can also plot a histogram of one of the statitistics if histobins is greater than zero. More about these four test statistics and other information can be found in the vignette. This function will not usually be called directly by the user. Instead, call hwx.test with method set to either “auto” or “monte”.
mtest(c, ntrials = 1e+05, statName = "LLR", histobins = 0,
histobounds = c(0, 0), showCurve = T, safeSecs = 100, detail = 2)A matrix containing the genotype counts. It should be a square matrix, but only the lower-left half is used.
the number of random trials to perform
can be “LLR”, “Prob”, “U”, or “Chisq” depending on which one is to be ploted. Note that P values for all four are computed regardless of which one is specified with this parameter.
If 0 no histogram is plotted. If 1 or TRUE a histogram with 500 bins is plotted. If set to a number greater than 1, a histogram with histobins is plotted.
A vector containing the left and right boundaries for the histogram's x axis. If you leave this as the default, c(0,0), then mtest will compute reasonable bounds to include most of the distribution.
whether to show a blue curve indicating the asymptotic (chi squared) distribution. This only works for LLR and Chisq
After this many seconds the calculation will be aborted. This is a safety valve to prevent attempts to compute impossibly large sets of tables.
Determines how much detail is printed. If it is set to 0, nothing is printed (useful if you use mtest programmatically.).
mtest returns a list components
The four computed P values corresponding to the test statistics: LLR, Prob, U and Chisq in that order.
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Standard errors for the P values. These come from the binomial.
The four observed statistics in the same order as above
The number of tables examined during the calculation
The input matrix of genotype counts
The allele counts \(m\) corresponding to the input genotype counts
Which test statistic was used if a histogram was plotted
If greater than zero, the number of bins to use for the histogram
The lower and upper limits of the test statistic in the histogram
Vector of \(histobins\) values for the histogram
Whether the asymptotic curve should be plotted with the histogram
The methods are described by Engels, 2009. Genetics 183:1431.