chi.squared {snpMatrix} | R Documentation |
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)
x |
An object of class "snp.tests.single" ,
"snp.tests.single.score" , or "snp.tests.glm" |
df |
Either the numeric value 1 or 2 |
simplify |
This switch is relevant when x is of class
"snp.tests.glm" and plays the same role as it does in
sapply . If simplify=TRUE , where possible
the output is returned as a simple numeric vector rather than as a
list |
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 snp.tests.glm
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.
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 david.clayton@cimr.cam.ac.uk
single.snp.tests
,
snp.lhs.tests
, snp.rhs.tests
,
snp.tests.single-class
,
snp.tests.single.score-class
,
snp.tests.glm-class
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)