From: Use of partial least squares regression to impute SNP genotypes in Italian Cattle breeds
 | Number of SNP |  | Imputation accuracy (PLSR) | Imputation accuracy (Beagle) | ||||
---|---|---|---|---|---|---|---|---|
Chromosome | 50K | 3K | 7K | Â | 3K | 7K | 3K | 7K |
1 | 2814 | 146 | 320 | Â | 0.916 | 0.953 | 0.876 | 0.919 |
2 | 2294 | 119 | 277 | Â | 0.911 | 0.951 | 0.863 | 0.922 |
3 | 2191 | 107 | 261 | Â | 0.897 | 0.944 | 0.846 | 0.898 |
4 | 2123 | 106 | 237 | Â | 0.903 | 0.941 | 0.861 | 0.908 |
5 | 1812 | 107 | 233 | Â | 0.912 | 0.948 | 0.872 | 0.912 |
6 | 2164 | 109 | 254 | Â | 0.908 | 0.953 | 0.867 | 0.914 |
7 | 1876 | 95 | 215 | Â | 0.908 | 0.949 | 0.858 | 0.915 |
8 | 2026 | 104 | 232 | Â | 0.919 | 0.953 | 0.872 | 0.915 |
9 | 1708 | 92 | 214 | Â | 0.904 | 0.949 | 0.851 | 0.909 |
10 | 1841 | 97 | 209 | Â | 0.909 | 0.946 | 0.872 | 0.915 |
11 | 1913 | 91 | 222 | Â | 0.901 | 0.947 | 0.862 | 0.914 |
12 | 1408 | 85 | 175 | Â | 0.903 | 0.942 | 0.856 | 0.899 |
13 | 1486 | 75 | 166 | Â | 0.910 | 0.949 | 0.860 | 0.911 |
14 | 1453 | 70 | 166 | Â | 0.897 | 0.945 | 0.850 | 0.912 |
15 | 1427 | 74 | 167 | Â | 0.898 | 0.945 | 0.864 | 0.915 |
16 | 1337 | 74 | 160 | Â | 0.910 | 0.950 | 0.864 | 0.913 |
17 | 1367 | 65 | 156 | Â | 0.888 | 0.936 | 0.842 | 0.900 |
18 | 1147 | 59 | 136 | Â | 0.877 | 0.924 | 0.825 | 0.884 |
19 | 1164 | 56 | 143 | Â | 0.878 | 0.935 | 0.827 | 0.895 |
20 | 1351 | 70 | 172 | Â | 0.921 | 0.960 | 0.886 | 0.933 |
21 | 1170 | 58 | 134 | Â | 0.881 | 0.934 | 0.832 | 0.899 |
22 | 1087 | 57 | 133 | Â | 0.894 | 0.941 | 0.849 | 0.900 |
23 | 919 | 47 | 118 | Â | 0.887 | 0.938 | 0.842 | 0.895 |
24 | 1072 | 54 | 135 | Â | 0.888 | 0.941 | 0.842 | 0.903 |
25 | 831 | 41 | 109 | Â | 0.865 | 0.926 | 0.816 | 0.887 |
26 | 905 | 45 | 102 | Â | 0.889 | 0.931 | 0.841 | 0.890 |
27 | 834 | 41 | 100 | Â | 0.872 | 0.924 | 0.832 | 0.890 |
28 | 806 | 46 | 99 | Â | 0.871 | 0.922 | 0.826 | 0.879 |
29 | 901 | 47 | 110 | Â | 0.875 | 0.934 | 0.828 | 0.888 |
Total SNP | 43427 | 2237 | 5155 | Mean | 0.896 | 0.942 | 0.851 | 0.905 |