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Table 2 Summary of training set sizes derived from the data sets outlined in TableĀ  1

From: MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing

Training set name Positive set (Iter. 1, Iter. 2, Iter. 3) Negative set (Iter. 1, Iter. 2, Iter 3.)
Disease negative set DM-SAVs (1,189, 1,189, 2,601) DM-SNVs (7,729, 7,363, 31,967)
SNP negative set DM-SAVs (1,189, 1,189, 2,090) SNP-SNVs (7,339, 7,253, 70,847)
Mixed negative set (disease and SNP) DM-SAVs (1,189, 1,189, 6,335) DM-SNVs and SNP-SNVs (15,068, 14,616, 111,630)
Random SNP set (control) SNP-SNVs (50%) (3,669, 3,669, 9,901) SNP-SNVs (50%) (3,670, 3,613, 7,349)
  1. Number of training examples for each different iteration (iter. 1, iter. 2 and iter. 3.) are shown in parentheses.