**0**wrote:

Hi there, i am processing a genome-wide methylation data, and i wanna to find out which chromosome were enriched with differentially methylated probes(dmp). I noticed a research compared the distribution of dmps located on each chromosome.

for example, 8.87% of CpG probes on Chromosome 13 were identified as Bonferroni-significant dDMPs (relative enrichment = 1.26, P = 3.68 × 10−10), whereas only 4.09% of CpG probes on Chromosome 19 reach this criterion (relative enrichment = 0.55, P = 7.01 × 10−79).

(reference: Spiers H, Hannon E, Schalkwyk LC, et al. Methylomic trajectories across human fetal brain development. Genome Research. 2015;25(3):338-352. doi:10.1101/gr.180273.114.)

The METHOD part mentioned that the enrichment analysis was done by fisher's exact test, so i try to use fisher.test in R to replicate the result. However, i get a same P value but i have no idea how to caculate the enrichment score. The imput data as following:

```
Chromosome TotalProbes SignificantProbes (%) Enrichment(95% CI) p value
1 40079 3109 (7.76) 1.09 (1.04 -1.13) 3.56E-05
Total 399364 28718 (7.19) NA NA
```

The METHOD part mentioned that the enrichment analysis was done by fisher's exact test, so i try to use fisher.test in R to replicate the result. However, **i get a same P value but i have no clue how to caculate the enrichment score.**
Any idea? Any suggestion will be appreciated!

```
> x<-c(40079-3109,3109,399364-28718,28718)
> dim(x)<-c(2,2)
> fisher.test(x)
Fisher's Exact Test for Count Data
data: x
p-value = 3.558e-05
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
0.8864884 0.9578336
sample estimates:
odds ratio
0.9213249
```

odds ratio gives you the enrichment.

9.0kThanks for your reply. But my OR is 0.92 (95%CI: 0.886-0.958) differs from the enrichment score in paper: enrichment score=1.09 (1.04 -1.13). I used the same input with the research, and our p values are consistent. Do i miss any steps?

0