Table 1. List of 11 cell line pairs detected to have very similar genotype proﬁles, evaluated on a set of 5.3K SNPs Cell line name (CL1) M14 MCF7 MCF7 NCI.ADR.RES NCI.H460 SNB.19 184A1 BT.20 H1450 H1450 H2141 Cell line name (CL2) MDA.MB435 BT.20 KPL.1 OVCAR.8 H2195 U251 184B5 KPL.1 H2141 H220 H220 Nucleic Acids Research, 2008, Vol. 36, No. 7 2453 No of mismatches Homozygous (AA)– Homozygous (BB) [or vice versa] Homozygous (AA or BB)– Heterozygous (AB) [or vice versa] 2 0 0 0 0 0 37 1 0 0 0 311 115 114 35 250 180 523 134 42 0 40 Distance D Percentage of valid calls 0.0747 0.0279 0.0271 0.0076 0.0680 0.0394 0.1084 0.0308 0.0092 0.0000 0.0088 0.794 0.781 0.797 0.874 0.696 0.866 0.978 0.831 0.866 0.861 0.857 0.2649–0.4891 0.3774–0.5765 0.44–0.86 0.37–0.90 0.28–0.94 0.20–1 Table 2. Summary of pair-wise distances/diﬀerences varying the number of SNPs Number of SNPs Mean distance D (SD) Min–max distance D Mean distance D (SD) Min–max distance D Set of CLs (133) used for the SNP selection process Set of CLs (13) used for independent validation 58 000a 5279b 80 60 40 20 0.3832 (0.0347) 0.4723 (0.0328) 0.66 (0.06) 0.66 (0.07) 0.66 (0.09) 0.66 (0.12) CL, cell line. aSet of SNPs represented on the 50K Xba chip. bSet of ﬁltered SNPs, used for the selection of the best SNPs. ‘similar’ (see Figure 4, Panels B and C). With 40 SNPs, 9 real pairs were scored ‘similar’, and one real pair was scored ‘uncertain’ (see Figure 4, Panel D). Using the panel of 20 SNPs a few cell lines were mis-scored as ‘similar’, suggesting that this number of SNPs is insuﬃcient for accurate identity determination. To further prove the eﬃcacy of the SNP selection process with the goal of deﬁning an optimal SNP panel, we ran a ‘baseline experiment’, randomly selecting four sets of SNPs comprised of either 80, 60, 40 or 20 SNPs taken from the 5.3 K ﬁltered set. We measured the pair-wise distances on the two sets of cell lines as reported in Table 2. The mean distance values are similar to the 5.3 K set mean distances but the standard deviations from the means are larger compared to the experiments with the selected SNP panels. Furthermore, in the randomly selected trials unrelated samples were detected as having exactly the same genotype calls for all the considered SNPs (see Supplementary Table 3). These experiments suggest the limitation of using randomly selected SNPs for the development of an identiﬁcation test. These results suggest that any set of 40 SNPs selected from the top 100 SNPs, listed in Supplementary Table 2, provides researchers with a good SNP panel for DNA sample identiﬁcation. However, the more SNPs 0.4227 (0.0330) 0.4967 (0.0337) 0.65 (0.06) 0.65 (0.06) 0.65 (0.08) 0.64 (0.11) 0.3613–0.4962 0.4274–0.5699 0.49–0.78 0.50–0.77 0.46–0.85 0.40–0.90 in the panel, the more conﬁdent one can be in the ﬁnal call. Distance between different cell line passages A common concern cited with use of cell lines regards genetic changes that occur during in vitro cultivation. Cell line genomic stability when going from one passage to the next can be assessed by comparing genomic proﬁles. The ability to determine relatedness between samples suggests that the SPIA distance score may be useful in characteriz- ing genetic drift of cell lines over time in culture. In order to ﬁrst assess genetic stability over time and secondly to evaluate the capability of SPIA assay to correctly identify them regardless of the passage number, we genotyped and studied two prostate cell lines, N15C6 and N33B2 (21), over multiple passages using 50 K Xba Aﬃmetrix arrays. We ran SPIA on diﬀerent passages using 40 SNPs out of the top 100 SNPs. The pair-wise distances were all equal to zero (probabilistic test scores ‘similar’), suggesting that our approach can correctly identify one cell line, regard- less of the passage. Interestingly, when extensively looking at the 50 K data we noticed that, where the N33B2 was very stable all along the genome, the cell line N15C6 exhibits genetic instability. The distance between passage 48 and passage 63 along chromosome 11 was about 0.2,