similar to: AMOVA in R

Hi! I am trying to analyse my data using amova (http://www.oga-lab.net/RGM2/func.php?rd_id=pegas:amova): My input to R is a DNA sequence file, format=fasta dna<- read.dna("XX.fasta", format="fasta") #left other options as default d<- dist.dna(dna, model="raw") g<- read.table("XXX.design") Load necessary libraries: library(pegas)

Hello, I am trying to run some AMOVA analyses with the amova function in the package ade4. When running the example dataset provided in ade4, I noticed a difference between the published results from the same data (Excoffier et al. 1992) and what ade4 calculates. Below are the data for "within sample/population" from ade4 and from the haplotypic distance matrix in the paper:

Hello, I am interested in using the amova function of ade4 package of R. I would like to know if there is any possibility to perform an amova with a specific anova model, as a factorial anova with some factors nested, or, if this could not be done, how could I perform an anova with my specific model but with molecular distance data? I would be very grateful if you could help me with this fact in

Dear All, I'd like to perform adonis (from the vegan package) rather than amova (in ade4) on some haplotype data, as I have crossed factors. Is there a simple way to tweak the source to allow weights (haplotype frequencies) in a similar way to amova? Best Simon

Was there ever an answer to this question about how to do amova with factorial data? t hundley [[alternative HTML version deleted]]

The ade4 package (v. 1.2-1) has been updated on CRAN. New features include: - functions based on Rao's axiomatization of diversity measures : Rao's diversity coefficient and dissimilarity coefficient (divc and disc) - functions based on Excoffier et al. analysis of molecular variance with tests of the difference among the factors (amova). - functions introducing double principal

The ade4 package (v. 1.2-1) has been updated on CRAN. New features include: - functions based on Rao's axiomatization of diversity measures : Rao's diversity coefficient and dissimilarity coefficient (divc and disc) - functions based on Excoffier et al. analysis of molecular variance with tests of the difference among the factors (amova). - functions introducing double principal

Hi, For the last few days I have tried utilise your package "pegas" in order to obtain some values for indices like the nuclear diversity and tajimas d value. I have modified my dataset (a text file containing dna sequences) in order to be able to read it in with the tools provided by pegas. Here, I have oriented myself on the description provided by the help-page in read.loci().

Hi, I am new to clustering and was wondering why pvclust using "maximum" as distance measure nearly always results in p-values above 95%. I wrote an example programme which demonstrates this effect. I uploaded a PDF showing the results Here is the code which produces the PDF file: ------------------------------------------------------------------------------------- s <-

Hi the list, A new version (0.92) of my package 'noia' will be available soon on CRAN mirrors, and I think it might be a good opportunity to introduce it shortly to the R community. In summary: 'noia' will be of absolutely no interest for 99.99% of you. The 0.01% remaining are quantitative geneticists who are interested in measuring the effect of genes in a proper way. Since

Hi the list, A new version (0.92) of my package 'noia' will be available soon on CRAN mirrors, and I think it might be a good opportunity to introduce it shortly to the R community. In summary: 'noia' will be of absolutely no interest for 99.99% of you. The 0.01% remaining are quantitative geneticists who are interested in measuring the effect of genes in a proper way. Since

Dear friends, I would like to announce for tests and free use a good add-on for Samba. It is a LAN-based interface for famous Pegasus Mail by David Harris, emulating his Mercury MTA. Note that this message have passed through this system. Look in headers. It is working! http://www.cor.neva.ru/~aal/pegas/pegas+qmail-1_0.tar.gz (7k) The file contains the patch against qmail 1.03, source of

Hi, I'm having some difficulties formulating this question. But what I want, is to extract the options associated with a parameter for a function. e.g. method = c("Nelder-Mead", "BFGS", "CG", "L-BFGS-B", "SANN") in the optim function. So I would like to have a vector with c("Nelder-Mead", "BFGS", "CG",

Un saludo R-inómanos: Les escribo porque tengo una duda que no he podido resolver por mis medios y actuales conocimientos. He querido instalar el paquete "ade4" en R (OP linux-ubuntu) pero no he podido por un error que según entiendo está relacionado con una librería. Me permito mostrarles el texto que me aparece luego de tratar de instalarlo desde los repositorios: >

Hi, I'm trying to build a thesaurus that will sensible values for rare words. I suspect the best algorithm to use is k-means although I'm not sure about that -- I would have preferred a k dimensional space with a binary cluster in each dimension so a word can belong to 0..k clusters, but I digress... I can measure the strength of correlation between words fairly easily by counting

Hello, Thanks James for the reply. That cleared a few things out. Apologies for replying late because of exams going on. I was going through the previous clustering API to understand how it worked and it seems like the the approach for construction of the termlists which are used for distance metrics use TF-IDF weighting with cosine similarity, which is very similar to the approach I would need

Hello, The ade4 package is now available on CRAN. ade4 is a multivariate data analysis package oriented towards statistical ecology. The main functions include one-table (PCA, COA, MCA, PCO, etc.), two-tables (PCAIV, Co-inertia, CCA, etc.) and k-tables multivariate analysis methods, with several Monte-Carlo tests and many graphical display methods. A complete documentation with many example data

Hello, The ade4 package is now available on CRAN. ade4 is a multivariate data analysis package oriented towards statistical ecology. The main functions include one-table (PCA, COA, MCA, PCO, etc.), two-tables (PCAIV, Co-inertia, CCA, etc.) and k-tables multivariate analysis methods, with several Monte-Carlo tests and many graphical display methods. A complete documentation with many example data

Hey Parth, Thanks for the reply. I am considering implementing a cosine distance metric too, along with euclidian distance because of the dimensionality issue that comes in with K-Means and euclidian distance metric. That does help when we deal with sparse vectors for documents. The particular problem I'm having is representing centroids in an efficient way. For example, when we find the mean

Dear R-Users, ade4TkGUI is a new package available on CRAN. It implements a Tcl/Tk graphical user interface (GUI) for the ade4 package. Only the most basic functions of ade4 have a GUI in this first version : classical one-table data analysis methods (PCA, COA, MCA, PCO, etc.), one table with groups of rows (BGA, WGA, DA), and two-tables analysis methods (Coinertia analysis, CCA, PCAIV).