They could show that cross-platform comparability is improved when the transcriptome is analyzed by a transcript-specific approach and a minimum probe set size of four is used.
We found that the probe sequences on the HG-U133A were sufficient to distinguish multiple transcript intensities for 215 genes (or 141 genes with a minimum probe set size of 3).
Modeling the Z parameter requires multiple set sizes at minimum, one set size that is below capacity and one set size above capacity.
Maximum size of gene sets was set to 500 genes and minimum gene set size was set to 15. Empirical significance values were calculated using 10,000 permutations.
With a minimum gene set size of 15 and maximum gene set size of 200, 297 gene sets of the original 431 were used in the analysis.
With a minimum gene set size of 15 and maximum gene set size of 200, 3,076 gene sets out of the original 4,722 were used in the analysis.
For toy datasets generated from the OVA model, the minimum predictor set size necessary to differentiate among the K classes is K - 1.
The parameters used were: 1000 permutations using the C5 gene sets (GO gene sets), the diff_of_classes algorithm as metric for ranking genes, weighted enrichment statistic, minimum gene set size of 3. Other parameters were set as default.
Weighted enrichment statistics were calculated by the GSEA software, using a minimum gene set size of 5 to account for the limited number of genes assayed by the Goldengate Cancer Panel.
