Extract test statistics and p-values
Generic functions to extract values from the SNP association test objects returned by various testing functions
chi.squared(x, df) deg.freedom(x) effect.sign(x, simplify) p.value(x, df) sample.size(x) effective.sample.size(x)
x |
An object of class |
df |
Either the numeric value 1 or 2 (not used when |
simplify |
This switch is relevant when |
These functions operate on objects created by
single.snp.tests, snp.lhs.tests, and
snp.lhs.tests.
The functions chi.squared and p.value return the
chi-squared statistic and the corresponding p-value.
The argument df is only used for
output from single.snp.tests, since this function calculates
both 1 df and 2 df tests for each SNP. The functions
snp.lhs.tests and snp.rhs.tests potentially calculate
chi-squared tests on varying degrees of freedom, which can be
extracted with deg.freedom. The function effect.sign
indicates the direction of
associations. When applied to an output object from
snp.single.tests, it returns +1 if the association, as
measured by the 1 df test, is positive and -1 if the
association is negative. Each test calculated by GlmTests
are potentially tests of several parameters so that the effect sign
can be a vector. Thus effect.sign returns a list of sign
vectors unless, if simplify=TRUE, and it can be simplified as a
single vector with one sign for each test.
The function sample.size returns the number of observations
actually used in the test, after exclusions due to missing data have
been applied, and effective.sample.size returns the effective
sample size which is less than the true sample size for tests on
imperfectly imputed SNPs.
A numeric vector containing the
chi-squared test statistics or p-values. The output vector has a names
attribute.
The df and simplify arguments are not always
required (or legal). See above
David Clayton dc208@cam.ac.uk
data(testdata) tests <- single.snp.tests(cc, stratum=region, data=subject.data, snp.data=Autosomes, snp.subset=1:10) chi.squared(tests, 1) p.value(tests, 1)
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