Next, we used genotyping arrays to detect copy number alterations (CNAs) between the iPSC lines and their progenitor fibroblasts. For this purpose, we developed a computational approach10 that can detect genetic abnormalities of >200 Kb occurring in 20% or more cells. We identified trisomies in 4% of lines (none of the selected lines), and 41% of lines (18% of the selected lines) harboured one or more CNAs of, on average, 7.15 Mb in length with duplications outnumbering deletions by 2.8 to 1 (Fig. 1e, Supplementary Table 2). Although the majority of CNAs were unique to single iPSC lines, 22% were also observed in at least one replicate line from the same donor (at least one base pair overlap), and 15% were identified in all replicates (Fig. 1f). We found no significant association between the number of CNAs and either passage number, donor age, gender or PluriTest score of a line (P > 0.09, Fig. 1g, Extended Data Fig. 3).
