Table 2 Summary of training set sizes derived from the data sets outlined in Table 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) |