I would like to develop a test to identify which variables in my data set have a variation higher than the "average variability".
I'm struggling with that since days, and I also tried in vain to look for help in other forums.
I have data from biological experiments, that look like this:
v1 2 1.8 1.5 1.9 2.1 1.78 1.95 2.0 2.1 v2 2 100 -5.2 v3 1 -1.3 -2 2.3 v4 1 1.5 1.6 1.9 2.1 2.0 2.4 -1.1 2.3 1.5 1.6 1.9 1.8 1.6
These represent gene expressions. Now, I would expect that all values of each variable(genes) are more or less similar, since the values are repeat measurements of the same gene.
Having a variable with such a huge difference, as v2 , doesn't have sense, because the repeated measurements should give consistent values. Therefore, it has to come from a methodological error and the variable (gene) has to be discarded.
I was looking for a method (possible a statistical test) in R which could identify the "average variability" among my samples and report me which variables (genes) have a variability significantly greater. This means that for these genes my data are not good enough to estimate the expression, and I have to discard them.
I would really appreciate any suggestion/links/advice/methods on test I could use for my purpose.