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Only one cluster, containing six protein-coding genes, contained genes whose expression levels decreased with a similar amplitude (Fig. 4) as the genes represented by the mean cluster values shown in Figure 3.
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Reactions with times more than 2 standard deviations beyond the mean cluster value were considered failures and repeated.
As this data did not include samples from all the populations used to construct the DNA pools, the mean cluster position values were also derived from the genotype classes of 106 individuals originating from 8 populations across the study area (Rivers: Alta, Laukhelle, Iesjoki, Kola, Varzuga, Onega, Pechora Unya and Narva).
The mean cluster size and p-values are presented in see Additional File 1, Supplement Table S12.
However, when a Ar flow rate reach some value the mean cluster size decreases since Ar will also sweep the cluster through the aggregation zone more rapidly, this reducing the time for particle growth.
It was found that Ar flow rate favors the cluster growth but when this flow reach some critical value the mean cluster size decreases since Ar also sweep the cluster through the aggregation zone this reducing the time for particle growth.
Based on this information, we used the Genesis program to perform k-means clustering, imposing values of k that ranged from 26 40.
To overcome this problem, we perform k-means clustering on the values of the PCA coefficient, a i, instead of the values of the raw data, w i.
c-means clustering computes membership values for each tile towards all the clusters and all the membership values add up to 1.
Figure 3 K -means clustering – Mean values of the C V of the unit test case metrics.
Hierarchical and k-means clustering of RQ values was performed using the TIGR MeV software suite [16].
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