A novel analysis strategy for integrating methylation and expression data reveals core pathways for thyroid cancer aetiology

Table 4 Ranking comparison for 15% threshold level; between positive correlation, inverse correlation and all together.

	Model 7 (>15% Methylation Change, Significances Combined)	Model 8 (>15% Methylation Change, Inverse Correlated,Significances Combined)	Model 9 (>15% Methylation Change, Positively Correlated,Significances Combined)
KEGG TERMs	Pooled Dataset	Pooled Dataset	Pooled Dataset
MAPK Signalling	6	59	7
ECM Receptor	3	7	4
ErbB Signalling	10	4	5
NF-KB Signalling	22	11	-
Wnt-β-Catenin Signalling	72	-	-
VEGF Signalling	30	60	53
Thyroid Cancer	45	65	27
Adherens Junction	14	10	11
p53 Signalling	54	25	-
TGF-beta Signalling	13	-	42
Notch Signalling	12	55	49
GnRH Signalling	56	37	50
Neurotrophin Signalling	17	21	6
Focal Adhesion	2	2	1
Transcr. Misregulation	51	65	-
Apoptosis	4	1	-
Pathways in Cancer	1	3	3
Toll-like receptor signalling pathway	8	5	-
Pentose-phosphate pathway	18	17	15

Rankings of KEGG functional enrichment results on pooled dataset to investigate the differences between positive and inverse correlation. When only inverse correlated genes were taken, we observed 9 pathways in top 20 rankings and when only positively correlated genes were taken, we observed 8 pathways in top 20 rankings. On the other hand, when no filter applied and all genes above the 15% threshold were taken, we reached the optimal analysis model with 12 pathways in top 20.

ISSN: 1471-2164