Table 1

Optimal SNP subsets using LDA or sIB for predicting psoriasis with average accuracy and 95% confidence interval estimated from Bootstrap re-sampling

Subsets

Components (dbSNP_rs on chromosome)

CV HMSS (Bootstrap mean and 95% CI)

Total CV accuracy (Bootstrap mean and 95% CI)

Test HMSS (Bootstrap mean and 95% CI)

Total test accuracy (Bootstrap mean and 95% CI)


LDA


1 SNP*

rs10905106 on 10

0.498(0.498, 0.475-0.518)

0.495(0.496, 0.474-0.516)

0.544(0.494, 0.469-0.519)

0.553(0.508, 0.486-0.532)


2 SNPs*

rs10958357 on 8 rs7973936 on 12

0.486(0.499, 0.480-0.520)

0.495(0.500, 0.481-0.521)

0.556(0.498, 0.471-0.525)

0.565(0.512, 0.491-0.535)


1 SNP

rs4375421 on 11

0.540(0.497, 0.474-0.519)

0.540(0.498, 0.476-0.518)

0.492(0.500, 0.476-0.529)

0.491(0.499, 0.474-0.529)


2 SNPs

rs950753 on 3 rs7058025 on X

0.570(0.493, 0.468-0.514)

0.575(0.508, 0.486-0.530)

0.463(0.476, 0.451-0.502)

0.459(0.473, 0.450-0.498)


FS

38 SNPs

0.604(0.500, 0.478-0.520)

0.622(0.503, 0.482-0.523)

0.520(0.496, 0.472-0.524)

0.514(0.491, 0.466-0.518)


SFFS

32 SNPs

0.622(0.497, 0.475-0.520)

0.622(0.502, 0.479-0.525)

0.512(0.498, 0.472-0.523)

0.509(0.498, 0.473-0.522)


sIB


1 SNP*

rs12191877 on 6

0.611(0.605, 0.563-0.630)

0.611(0.608, 0.580-0.631)

0.668(0.668, 0.641-0.694)

0.699(0.698, 0.676-0.720)


2 SNPs*

rs12191877 on 6 rs4953658 on 2

0.557(0.444, 0.014-0.633)

0.574(0.550, 0.426-0.633)

0.674(0.674, 0.650-0.698)

0.685(0.684, 0.662-0.707)


FS

rs12191877 on 6

0.611(0.605, 0.563-0.630)

0.611(0.608, 0.580-0.631)

0.668(0.668, 0.641-0.694)

0.699(0.698, 0.676-0.720)


SFFS

rs2844627 on 6 rs7773175 on 6

0.619(0.617, 0.576-0.641)

0.616(0.615, 0.585-0.638)

0.659(0.658, 0.633-0.683)

0.677(0.676, 0.655-0.699)


* The best test HMSS among all subsets

Test HMSS for the subset with the best CV HMSS

Fang et al. BMC Dermatology 2011 11:1   doi:10.1186/1471-5945-11-1

Open Data