Dear Sarah,
Thanks for your reply. But I don't have any site where all the species
are 0. Is there anyway to calculate the dissimilarity between sites where
it computes only the non-zero species values. Excluding all the zero event
will result a big loss in species data. I don't want to delete the cases
where may be 5out of 8 sites have species info, only 3 don't have.
Should I replace zero with a very small number. What is the best thing to
do in such cases?
Thanks,
Mitra
On 24 June 2013 21:24, Sarah Goslee <sarah.gos...@gmail.com> wrote:
> Hi,
>
> What do you expect the dissimilarity between a site with no species
> and a site with some species to be?
>
> If you want to use Bray-Curtis dissimilarity, you need to drop the
> sites with no species, as the error message suggests.
>
> But if you can answer my first question, you may be able to select a
> different dissimilarity metric that matches your expectations
> numerically.
>
> Sarah
>
>
> On Mon, Jun 24, 2013 at 7:33 AM, Suparna Mitra
> <suparna.mitra...@gmail.com> wrote:
> > H
> > ello R-experts,
> > I want to do ordination plots using vegan metaMDS.
> > I have a where many cells have zero values.
> >
> > Data structure:
> > X[1:10,1:14]
> > Height.1 Height.2 Height.3 Height.4 Height.5 Height.6 Height.7
> > Height.8 Height.9 Height.10 Height.11 Height.12 Height.13
> > D30I1A 46 0 0 0 0 0 0
> > 0 0 0 39 0 98
> > D30I1B 46 0 0 0 0 0 0
> > 0 0 0 39 0 98
> > D30I1C 70 0 0 0 0 0 0
> > 0 0 0 0 85 0
> > D30I2A 47 0 0 0 0 0 0
> > 0 0 0 49 0 105
> > D30I2B 68 0 0 0 0 0 0
> > 0 0 0 83 0 214
> > D30I2C 0 75 0 0 0 0 0
> > 0 0 0 0 83 0
> > D30I3A 48 0 0 0 0 0 0
> > 0 0 0 42 0 107
> > D30I3B 64 0 0 0 0 0 0
> > 0 0 0 72 0 177
> > D30I3C 72 0 0 0 0 0 0
> > 0 0 0 0 96 0
> > D30M1A 60 0 0 0 0 0 0
> > 0 0 0 74 0 169
> >
> > Another data structure
> >> Genus_data[1:10,1:14]
> > Sample Acanthamoeba Acidianus Aegilops Alphapapillomavirus Asfivirus
> > Brassica Buchnera Coprinellus Diaphorobacter Hartmannella Ignicoccus
> > 1 HS1_S1 0 0 0 0 0
> > 0 0 0 0 0 0
> > 2 HS2_S2 0 1 1 0 0
> > 0 0 0 0 1 0
> > 3 HS3_S3 0 0 0 1 0
> > 0 1 1 1 0 0
> > 4 HS4_S4 0 0 0 0 1
> > 0 0 0 0 0 0
> > 5 HS13_S5 0 0 0 0 0
> > 0 0 0 0 0 0
> > 6 HS14_S6 0 0 0 0 0
> > 1 0 0 0 0 0
> > 7 HS15_S7 0 0 0 0 0
> > 0 0 0 0 0 0
> > 8 HS16_S8 0 0 0 0 0
> > 0 0 0 0 0 1
> > 9 HS25_S9 1 0 0 0 0
> > 0 0 0 0 0 0
> >
> > I am having two different kind of errors for these two data...
> > Error 1
> >> ord1 <- metaMDS(
> > X
> > ="bray")
> > Square root transformation
> > Wisconsin double standardization
> > Error in if (any(dist < -sqrt(.Machine$double.eps))) warning("some
> > dissimilarities are negative -- is this intentional?") :
> > missing value where TRUE/FALSE needed
> > In addition: Warning messages:
> > 1: In distfun(comm, method = distance, ...) :
> > you have empty rows: their dissimilarities may be meaningless in method
> > bray
> > 2: In distfun(comm, method = distance, ...) : missing values in results
> >
> > Error 2
> > ord.data= metaMDS(data, distance="bray")
> > Error in if (any(autotransform, noshare > 0, wascores) && any(comm < 0))
> {
> > :
> > missing value where TRUE/FALSE needed
> > In addition: Warning message:
> > In Ops.factor(left, right) : < not meaningful for factors
> >
> > I searched all the details of metaMDS where it is suggested to avail the
> > argument 'zerodist'
> > So I tried both
> >
> > X.dist1 <- metaMDSdist(X, method="bray",zerodist = "ignore")
> > X.dist2 <- metaMDSdist(X, method="bray",zerodist = "add")
> >
> > Can Please help me with this.
> > Thanks,
> > Mitra
> >
>
> --
> Sarah Goslee
> http://www.functionaldiversity.org
>
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