A statistical method for excluding non-variable CpG sites in high-throughput DNA methylation profiling.
BACKGROUND
High-throughput DNA methylation arrays are likely to accelerate the pace of methylation biomarker discovery for a wide variety of diseases. A potential problem with a standard set of probes measuring the methylation status of CpG sites across the whole genome is that many sites may not show inter-individual methylation variation among the biosamples for the disease outcome being studied. Inclusion of these so-called "non-variable sites" will increase the risk of false discoveries and reduce statistical power to detect biologically relevant methylation markers.


RESULTS
We propose a method to estimate the proportion of non-variable CpG sites and eliminate those sites from further analyses. Our method is illustrated using data obtained by hybridizing DNA extracted from the peripheral blood mononuclear cells of 311 samples to an array assaying 1505 CpG sites. Results showed that a large proportion of the CpG sites did not show inter-individual variation in methylation.


CONCLUSIONS
Our method resulted in a substantial improvement in association signals between methylation sites and outcome variables while controlling the false discovery rate at the same level.
Meng
Hailong
H
Altria Client Services, Research Development & Engineering, Richmond, VA 23219, USA. hlmeng@yahoo.com
Joyce
Andrew R
AR
Adkins
Daniel E
DE
Basu
Priyadarshi
P
Jia
Yankai
Y
Li
Guoya
G
Sengupta
Tapas K
TK
Zedler
Barbara K
BK
Murrelle
E Lenn
EL
van den Oord
Edwin J C G
EJ
D018899:CpG Islands / Q000235:genetics*; D004247:DNA / Q000235:genetics*; D019175:DNA Methylation; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D015233:Models, Statistical
D004247:DNA