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We carried out Principal Coordinates Analyses (PCoA) for visualizing genetic differentiation between and within species samples, using the R package Polysat (Clark and Jasieniuk 2011).
Principal coordinates analyses (PCoA) of these markers clustered accessions based on different characters.
Principal coordinates analyses using these data show population differentiation across the populations sampled for this study (Fig. 1).
The 26 plant accessions were clustered using phenetic (Dice/UPGMA) and principal coordinates analyses (PCoA) of the AFLP data.
Genetic differentiation was further assessed using principal coordinates analyses (PCoA) calculated in GenAlEx on the pairwise ΦPT matrix.
Principal coordinates analyses (PCoA), Jackknife Environment Clusters analyses were conducted in an online software UniFrac (http://bmf2.colorado.edu/unifrac/index.psp) (Lozupone et al. 2006) which employs the genetic distances to evaluate the community similarity based on the gene sequences data.
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The population structure was examined by applying principal coordinate analyses.
Principal coordinate analyses (PCoA) were based on the binary Jaccard distances (Lozupone and Knight 2005).
Principal coordinate analyses (PCO) were conducted separately for methanogenic archaea and for eubacteria.
The matrix of Rogers' distances was used to perform principal coordinate analyses (Gower 1966).
Also, principal coordinate analyses (PCA) showed clear separation (62.5%) between summer and winter isolates.
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