Description Usage Arguments Details Value Author(s) References Examples
This function tests, for a series of loci, the hypothesis that
genotype frequencies follow the Hardy–Weinberg equilibrium.
hw.test
is a generic with methods for the classes
"loci"
and genind
. Note that the latter
replaces HWE.test.genind
in the adegenet package.
1 2 3 4 5 |
x |
an object of class |
B |
the number of replicates for the Monte Carlo procedure; for the regular HW test, set B = 0 (see details). |
... |
further arguments to be passed. |
This test can be performed with any level of ploidy. Two versions
of the test are available: the classical chi^2-test based
on the expected genotype frequencies calculated from the allelic
frequencies, and an exact test based on Monte Carlo permutations of
alleles (Guo and Thompson 1992). For the moment, the latter version is
available only for diploids. Set B = 0
if you want to skip the
second test.
A matrix with three or four columns with the chi^2-value,
the number of degrees of freedom, the associated P-value, and
possibly the P-value from the Monte Carlo test. The rows of
this matrix are the different loci in x
.
Main code by Emmanuel Paradis; wrapper for genind
objects by Thibaut Jombart.
Guo, S. W. and Thompson, E. A. (1992) Performing the exact test of Hardy–Weinberg proportion for multiple alleles. Biometrics, 48, 361–372.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 |
Loading required package: ape
Loading required package: adegenet
Loading required package: ade4
/// adegenet 2.0.1 is loaded ////////////
> overview: '?adegenet'
> tutorials/doc/questions: 'adegenetWeb()'
> bug reports/feature requests: adegenetIssues()
Attaching package: 'pegas'
The following object is masked from 'package:ade4':
amova
The following object is masked from 'package:ape':
mst
chi^2 df Pr(chi^2 >)
fca8 395.80006 120 0.000000e+00
fca23 239.34221 55 0.000000e+00
fca43 434.33397 45 0.000000e+00
fca45 66.11849 36 1.622163e-03
fca77 270.52066 66 0.000000e+00
fca78 402.80002 28 0.000000e+00
fca90 217.19836 66 0.000000e+00
fca96 193.36764 66 1.965095e-14
fca37 291.00731 153 1.209777e-10
chi^2 df Pr(chi^2 >) Pr.exact
fca8 395.80006 120 0.000000e+00 0
fca23 239.34221 55 0.000000e+00 0
fca43 434.33397 45 0.000000e+00 0
fca45 66.11849 36 1.622163e-03 0
fca77 270.52066 66 0.000000e+00 0
fca78 402.80002 28 0.000000e+00 0
fca90 217.19836 66 0.000000e+00 0
fca96 193.36764 66 1.965095e-14 0
fca37 291.00731 153 1.209777e-10 0
chi^2 df Pr(chi^2 >) Pr.exact
FCA742 183.86464 120 1.594495e-04 0.007
FCA723 103.12121 21 8.062440e-13 0.001
FCA740 74.20811 15 7.868073e-10 0.000
FCA441 41.33714 10 9.834077e-06 0.004
FCA391 76.09323 36 1.080868e-04 0.409
F98 120.42555 10 0.000000e+00 0.003
F53 119.13991 55 1.242116e-06 0.002
F124 90.44434 36 1.401578e-06 0.071
F146 12.45142 10 2.559795e-01 0.315
F85 122.68186 91 1.505069e-02 0.004
F42 134.42730 45 7.690482e-11 0.000
FCA453 21.65249 15 1.172451e-01 0.131
FCA741 11.60034 6 7.150214e-02 0.046
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