Table 1.
Dinucleotide model performance on different datasets
| Data set | nca | npb | Single nucleotide model (eq. 1) | Dinucleotide model (eq. 4)c | |
| Latin Square [20] | 42 | 248152 | PM | 0.17 ± 0.01 | 0.22 ± 0.01 |
| 248152 | MM | 0.40 ± 0.01 | 0.50 ± 0.01 | ||
| Golden spikein [16] | 6 | 195994 | PM | 0.20 ± 0.02 | 0.22 ± 0.02 |
| 195994 | MM | 0.46 ± 0.02 | 0.51 ± 0.02 | ||
| Leukemia [35] | 72 | 201800 | PM | 0.49 ± 0.06 | 0.55 ± 0.07 |
| 201800 | MM | 0.60 ± 0.04 | 0.69 ± 0.04 | ||
| Etoposide response [34] | 60 | 496468 | PM | 0.05 ± 0.04 | 0.08 ± 0.06 |
| 496468 | MM | 0.11 ± 0.06 | 0.16 ± 0.08 | ||
| BK knockout [36,37] | 20 | 496468 | PM | 0.09 ± 0.04 | 0.13 ± 0.04 |
| 496468 | MM | 0.29 ± 0.050 | 0.36 ± 0.06 |
R2 of Naef and Magnasco [15] model (Single nucleotide) and the dinucleotide model for the five data sets used in this study. Results presented as average R2 ± SD.
anc: number of chips.
bnp: number of probes.
c The differences in R2 between single nucleotide model and dinucleotide model are all statistically significant (p < 10-3) using paired one-sided Wilcoxon and t tests.