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Amplification of the six subsamples within the same bioreactor DNA pool was assayed under the same PCR conditions but at different annealing temperatures (44 to 49°C), yielding a total of 30 different pyrosequencing datasets in the five different technologies.
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We use two different gene expression datasets in the two analyses.
We then simulated a dataset based on the initial population and the final population allele frequencies, and the number of individuals sampled in our real dataset in the two populations.
The strong saturation observed could limit the usage of the PAML like software, it could be appropriate to split the dataset in the two groups to see if any more signal would emerge.
The difference in the stress patterns was directly attributed to the datasets used in the two analyses of stress inversion.
Figure 9 shows the results of the 3D probability-based ERT imaging applied to the datasets collected in the three zones marked in Figure 4.
These differences may be attributable to the vastly different datasets used in the two experiments.
For computational reasons, up to 10,000 of the Probesets with highest expression levels were selected from each of the datasets described in the four reports [ 5, 10- 12].
To provide a systems view of citrus host response to the HLB bacterial infection, the Pearson correlation coefficient (Pcc) method was used to infer the gene coexpression network using the four datasets reported in the four transcriptomic studies [ 5, 10- 12].
Of note, our model had better discrimination in a clinical trial dataset than in the two observational cohorts.
In addition, different B. napus EST datasets were used in the two studies which might also contribute to differences.
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