#====================================================================================
#OUTPUT#====================================================================================
#Convert genind to dataframe> df <- genind2df(ravenpop_DefvOth, sep="/")> strata(ravenpop_DefvOth) <- df> #AMOVA into object; will print automatically if you do not put into object> amova.result <- poppr.amova(ravenpop_DefvOth, hier = ~pop, clonecorrect = FALSE, within = TRUE,+ dist = NULL, squared = TRUE, freq = TRUE,+ correction = "quasieuclid", sep = "_", filter = FALSE,+ threshold = 0, algorithm = "farthest_neighbor", threads = 1L,+ missing = "loci", cutoff = 0.10, quiet = FALSE,+ method = c("ade4", "pegas"), nperm = 0)
Found 1081 missing values.
3 loci contained missing values greater than 10%
Removing 3 loci: CoBr24, CoBr09, Ck1_B6GDistance matrix is non-euclidean.Using quasieuclid correction method. See ?quasieuclid for details.Warning messages:1: In is.euclid(xdist) : Zero distance(s)2: In is.euclid(distmat) : Zero distance(s)
> #Print result> amova.result$callade4::amova(samples = xtab, distances = xdist, structures = xstruct)
$results Df Sum Sq Mean SqBetween pop 1 7.057667 7.057667Between samples Within pop 196 1216.040893 6.204290Within samples 198 1079.245295 5.450734Total 395 2302.343855 5.828719
$componentsofcovariance Sigma %Variations Between pop 0.01639835 0.2806057Variations Between samples Within pop 0.37677823 6.4473649Variations Within samples 5.45073382 93.2720294Total variations 5.84391039 100.0000000
$statphi PhiPhi-samples-total 0.067279706Phi-samples-pop 0.064655075Phi-pop-total 0.002806057
> #Test for p value> amova.test <- randtest(amova.result)> > #Plot amova.test> plot(amova.test)> > amova.testclass: krandtest lightkrandtest Monte-Carlo testsCall: randtest.amova(xtest = amova.result)
Number of tests: 3
Adjustment method for multiple comparisons: none Permutation number: 99 Test Obs Std.Obs Alter Pvalue1 Variations within samples 5.45073382 -3.7992722 less 0.012 Variations between samples 0.37677823 4.2037855 greater 0.013 Variations between pop 0.01639835 0.5285421 greater 0.23What, specifically, are the warning messages: In is.euclid(xdist) : Zero distance(s) and In is.euclid(distmat) : Zero distance(s)? (Highlighted aqua below)
This means that some samples in your data had no differences
between them. This is usually the case with clonal data, but can
also happen when there is a lot of missing data.
Does "alter" stand for "alternative hypothesis" - and if so, what is this actually set at? (highlighted yellow below)
Yes. This means that the alternative hypothesis is that the
observed value is less than or greater than random chance. You
might want to try using method = "pegas" for an alternative
presentation (which, honestly is a bit more user friendly:
https://rdrr.io/cran/pegas/man/amova.html)
Is the p-value exact? Is there any way to see this at more decimal points to get a more exact p-value? (highlighted green below)
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