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This multi-resolution dataset was analyzed using Principal Components Analysis (PCA) to identify the dominant variance structure in the dataset.
The alignment dataset was analyzed using maximum likelihood (ML), maximum parsimony (MP) and Bayesian methods.
In order to infer divergence times among C. monspeliensis lineages and reconstruct its colonization history across the Canarian archipelago, the dataset was analyzed using a relaxed Bayesian approach as implemented in BEAST v.1.6.1 [45], [45].
The dataset was analyzed using equally weighted parsimony in TNT [17], [18] with a heuristic search of 1,000 replicates of Wagner trees followed by tree bisection-reconnection (TBR) branch swapping.
The dataset was analyzed using different statistical tests.
The final dataset was analyzed using PROC MIXED in SAS.
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With the objective of identifying the hidden relationships between the most common accidents, the road accident dataset is analyzed using the association rules technique.
The 184 sequences of the gag dataset were analyzed using a similar approach.
The WGS dataset is analyzed using a software tool that we recently developed, called MAQGene [12].
If genes of interest are defined inconsistently across different annotations, it is recommended that the RNA-Seq dataset is analyzed using different gene models.
Phylogenetic relationships between the 110 treponeme OTUs detected in the entire subject dataset were analyzed using Neighbour Joining (NJ), Maximum Likelihood (ML) and Bayesian (BA) approaches.
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CEO of Professional Science Editing for Scientists @ prosciediting.com