Choosing right statistical test in genomics

Question

[kirillkirilenko]

I have a bed files contain coordinates of one specific type of repetitive DNA in a chromosome. e.g.

0   190 TEsI
2844    2881    TEsI
2881    2988    TEsI
...

Now I'm interested in few specific regions, they about 10 kb in length. My supervisor asked me to comment on whether or not there is statistical significance in number of these types of repetitive DNA in these regions. I've plotted this:

Red stripe shows the position of region, horizontal black and green dashed lines indicate mean value and mean value with standard deviation for the whole chromosome with bin sizes of 100 kb (because this plot covers about 100 kb). How to test null hypothesis (there is no significance) here? Thank you in advance

Answer 1

[Andrzej Zielezinski]

You can use a one-sample t-test or a one-sample z-test. Both these tests determine whether there is a significant difference between the mean of a sample (number of repetitive DNA in regions of your interest) and a known or hypothesized population mean (mean value of repetitive DNA in the whole chromosome).

Null hypothesis: the mean of the repetitive DNA is 1 (the value of the horizontal black line).

Alternative hypothesis: the mean of the repetitive DNA is not 1 (the value of the horizontal black line).

Answer 2

[Jean-Karim Heriche]

Isn't the difference in bar size sufficient for you to declare that this is relevant to the biology you're interested in? This question isn't going to be answered by a statistical test. It seems you're looking at counts in intervals so I believe you should be looking at discrete statistics like based on the Poisson distribution especially because counts seem to be low.