This document summarizes a presentation on functional meta-analysis. It outlines the data sources used, which include gene expression arrays from studies of psoriasis and dermatitis and miRNA sequencing data from TCGA. It also describes the different meta-analysis models tested, including fixed effect and random effect models. The results sections shows the results of applying these models to identify significantly enriched pathways for psoriasis/dermatitis and differences between tumor and normal samples. It concludes that functional meta-analysis is an efficient method to confirm and discover functional profiles across different studies and functional annotations.

1. Functional Meta-Analysis
XIII Symposium on Bioinformatics
May, 10th-13th 2016, Valencia
Francisco García García, fgarcia@cipf.es

2. Outline
1. Introduction
2. Data & Methods
3. Results
4. Conclussions

3. Introduction1

4. Introduction1

5. Introduction1

6. Introduction1

7. Introduction1

8. Data
Psoriasis and Dermatitis
○ Gene expression arrays
○ Human
○ Case vs. control
2
○ Without allergens
○ Selected platforms
P: 65
D: 36
P: 23
D: 18

9. Data
Tumors
○ TCGA
○ miRNA-Seq expression
2
○ tumoral vs. normal samples
○ Illumina HiSeq technology
T: 32
T: 20

10. Data2

11. Methods2
FDR

12. 2 Methods
Meta-Analysis models:
● Fixed effect
● Random effect:
○ DerSimonian-Laird
○ Hedges
○ Sidik-Jonkman
○ Schmidt & Hunter
○ Paule & Mandel

13. Results3
method over under sig.over sig.under sig.ov.LOR sig.un.LOR
FE 84 216 45 173 0 3
HE 78 223 27 165 0 3
HS 79 223 27 164 0 3
SJ 77 224 21 158 0 3
PM 79 223 25 163 0 3
DL 79 223 27 163 0 3
Level 1: psoriasis & dermatitis KEGG pathways
302 190 3
FDR < 0.05 | LOR | > 0.5

14. Results3
ID name LB* LOR* UB* adjust.p
hsa00730 Thiamine metabolism -0.943 -0.761 -0.579 0.0001
hsa00785 Lipoic acid metabolism -0.754 -0.576 -0.398 0.0001
hsa00680 Methane metabolism -0.645 -0.494 -0.344 0.0001
Level 2: psoriasis & dermatitis KEGG pathways
ID name SE* tau2 I2 H2
hsa00730 Thiamine metabolism 0.093 0.105 37.69 1.605
hsa00785 Lipoic acid metabolism 0.901 0.099 30.53 1.44
hsa00680 Methane metabolism 0.077 0.078 33.58 1.506
*LB: lower bound, UB: upper bound, LOR: log. Odds Ratio, SE: Standard Error

15. Results3
Level 3: psoriasis & dermatitis KEGG pathways

16. Results3
method over under sig.over sig.under sig.ov.LOR sig.un.LOR
FE 842 878 312 387 63 87
HE 843 879 272 3151 51 80
HS 840 882 272 321 51 75
SJ 841 881 198 274 41 67
PM 841 881 263 311 51 75
DL 839 883 261 308 50 72
Level 1: tumor vs. normal Reactome pathways
1722 569 122
FDR < 0.05 | LOR | > 0.5

17. Results3
method over under sig.over sig.under sig.ov.LOR sig.un.LOR
FE 350 394 133 169 0 2
HE 350 394 120 136 0 2
HS 350 394 123 139 0 2
SJ 350 394 104 117 0 2
PM 350 394 120 136 0 2
DL 350 394 120 136 0 2
Level 1: tumor vs. normal Molecular Function
744 256 2
FDR < 0.05 | LOR | > 0.5

18. Conclusions4
Efficient method to confirm and discover
functional profiles
Flexible for functional annotations, high
throughput technologies data and methods
Assessment of Genomic Studies

19. Acknowledgements
David Montaner
Cristina Escribano
Iván Ansari
Joaquín Dopazo
Francisco García-García

20. Any questions?