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We expect that the more complete the datasets, the more accurate the predictions will be.
Once the tracking is complete, the datasets are stitched together to obtain the big picture (the connectome).
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From the 27 patients that completed the study, a complete dataset was available.
For completeness, the complete datasets (including also the non overlapping probes) were also analyzed in parallel.
The RI of the complete dataset, the technical characters and the design characters were all around 0.59.
For the complete dataset, the score of the best ML trees found was −80231.7055.
Then, each of the completed datasets will be analysed using the proposed statistical method.
It works by estimating the complete dataset from the incomplete dataset.
In this study, SAM was used to identify differentially expressed genes for the complete dataset and the imputed dataset.
Therefore we performed all other analyses with the complete datasets, including the more variable regions.
In this study, k-means was used to do gene clustering for the complete datasets and the imputed datasets.
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