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However, the relationship between these two data sources has not been closely examined.
Comparison between these two data showed a significant difference (p = 0.03).
However, it is not always easy to distinguish between these two data types.
These statistics indicate systematic errors exist between these two data sets.
Using only the top genes identified by those techniques, we recomputed the correlation between these two data sets.
If the two sets of numbers marched in reverse lockstep say, a 2% rise in oil matched a 1% decline in stocks then the correlation between these two data sets would be -1.
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As a rule, differences between the mean intensities for these two data sets were statistically insignificant (t-test; P < 0.05).
An algorithm is then used to find the best transformation between the two coordinate systems using these two data sets.
Comparisons between these three data sources have to be interpreted with care.
To further investigate the differences between these three data sets, we computed the average distances by combining the genomes into four groups (fig. 5).
We also performed an indirect comparison between these six data sets by mapping the reads of each data set to the w Mel genome, calling variants, and then comparing variant calls across strains.
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