Dear Forum Members,
I have been analyzing correlations between ENCODE data and my own data. Specifically I have been looking at overlapping (or intersecting) coordinates between data sets to assess colocalization. Now, I would like to add some statistics to the analysis. The data is basically a number of colocalized features to a number of colocalized features generated by random iterations.
So e.g. I could have something like, 900 colocalize, 300 do not from my data, and then by random iterations 200 localize while 700 dont.
900 200
300 700
Is it strong enough to apply Fisher's exact test or should I opt for something different. I have approx. 60 of such four-value tables for which I need to determine statistical significance.
I appreciate any comments on this
I have been analyzing correlations between ENCODE data and my own data. Specifically I have been looking at overlapping (or intersecting) coordinates between data sets to assess colocalization. Now, I would like to add some statistics to the analysis. The data is basically a number of colocalized features to a number of colocalized features generated by random iterations.
So e.g. I could have something like, 900 colocalize, 300 do not from my data, and then by random iterations 200 localize while 700 dont.
900 200
300 700
Is it strong enough to apply Fisher's exact test or should I opt for something different. I have approx. 60 of such four-value tables for which I need to determine statistical significance.
I appreciate any comments on this
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