I have a list of genes and I am checking certain factors for each gene. I have individual scoring system for each factor for each gene. My final table/matrix looks like this:
Gene Factor1 Factor2 Factor3 Factor4 ALS 0.006 1.0 2.3 0.8 NCLS 0.09 0.8 1.8 0.18 MLB 0.4 0.0 1.8 0.78 BJ 1.1 0.0 0.75 0.18
The scores for each factor are independent and comparable to scores within that factor only, i.e., 1.1 is very good for
factor1, but may not be so good for
factor3. However, for any given factor, the higher the number the better.
What I am trying to achieve is a ranking of genes. From the example, ALS and MLB should be on the top because for ALS, factors 2-4 have highest values, for MLB,
factor2 is 0 but other factors have high values.
Can you suggest what statistics can be used on matrices like this to create a ranking and level of significance? Can I normalize the scores for each factor by calculating Standard Score/z-score (even though all of them don't follow a normal distribution)? What other normalization can be done? Can I instead rank the genes independently for each factor, and then somehow combine the ranks to create a final ranking?