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## Figure 10.
Number of predicted motifs and number of matches in ScerTF at 15% FDR, for RED. FIRE was run with default parameters (optimized for yeast), with ^{2 }(mutual-information scoring function; same as Figure 8), FIRE and MatrixREDUCEk = 5, 10, 20, 40 and 80 clusters, and the number of clusters that yields the highest
number of motifs was selected a posteriori for each dataset. MatrixREDUCE was run with default parameters, with seeds of length
7, 8 and 9. (Left) Average results of the three methods on the 24 yeast datasets.
(Center) RED^{2 }and FIRE. Number of predicted motifs that match a known motif at 15% FDR in the ScerTF
database for the 24 yeast datasets. The y-axis corresponds to the number achieved
by RED^{2 }and the x-axis to the number achieved by FIRE with the best clustering procedure.
Superimposed points are indicated by shading. RED^{2 }has more matches than FIRE in 21 datasets and fewer in three datasets, which gives
a sign test P value of 0.0003. (Right) RED^{2 }and MatrixREDUCE (same explanations as for the center panel). RED^{2 }has more matches than MatrixREDUCE for 22 datasets and is on par for the remaining
two, which gives a sign test P value of 4.77 × 10^{-7}.
Lajoie |