Thanks for that, just to confirm I therefore need to use: #if #geogdist is a geographic distance matrix #gen_dist is a genetic distance matrix #env_var are environmental variables
mypcnm<-pcnm(geogdist) mydbRDA<-capscale(gen_dist~env_var+Condition(mypcnm$vectors)) cheers Nevil On 22/09/2010 1:34 AM, Jari Oksanen wrote:
On 21/09/10 17:40 PM, "Nevil Amos"<nevil.a...@gmail.com> wrote:I am trying to use the cca/rda/capscale functions in vegan to analyse genetic distance data ( provided as a dist object calculated using dist.genpop in package adegenet) with geographic distance partialled out ( provided as a distance object using dist function in veganthis method is attempting to follow the method used by Geffen et al 2004 as suggested by Legendre and . FORTIN (2010). I cannot see how to introduce the Conditioning ( partialled) second dist matrix. as you can see from the code snippet below, the two dist objects are of the same dimensions. - I get an error using capscale: Error in qr.fitted(Q, Xbar) : 'qr' and 'y' must have the same number of rows or cca Error in weighted.mean.default(newX[, i], ...) : 'x' and 'w' must have the same length when using a conditioning distance object instead of a variable (Clade) of the same length as the constraints ( Latitude and Longitude) I would be grateful, for any pointers on this, ie which test is the appropriate one to use ( I believe capscale since it is "similar to distance-based redundancy analysis (Legendre& Anderson 1999)") and whether this test is indeed equivalent to the approach suggested by Legendre&Fortin, (Geffen et al used DISTLM).Nevil, You cannot use cca() for dissimilarity data. If you have dissimilarity data, you must use capscale() which runs db-RDA. Even there, your constraints (variables on the right hand side of the formula) must be rectangular data and not dissimilarities. AFAIK, people have changed their dissimilarities into a PCNM structure when they want to partial out the distance effect. That is one of the few original possibilities since data must be rectangular (rows and columns). Cheers, jari oksanen
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