Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). Objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples, i.e. 65 glioblastoma and 5 non-tumoral tissues. As MethylCap-seq coverages were limited, we focused on the inherent capacity of the methodology to detect methylated loci rather than a quantitative analysis. MethylCap-seq and HM450 data were dichotomized and performances were compared using a gold standard free Bayesian modelling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. In addition, genome-wide characteristics were compared, revealing that HM450 probes identified substantially fewer regions compared to MethylCap-seq. Although results indicated that the latter method can detect more potentially relevant DNA-methylation, this did not translate into the discovery of more differentially methylated loci between tumours and controls compared to HM450. Our results therefore indicate that both methodologies are complementary, with a higher sensitivity for HM450 and a far larger genome-wide coverage for MethylCap-seq, but also that a more comprehensive character does not automatically imply more significant results in biomarker studies.