I have a dataset of a list of genes with predicted scores (of likelihood to cause disease) from 2 different machine learning classifiers:
Gene Score1 Score2 RP11-983P164 0.2678077 0.2119513 SLC25A20 0.2644568 0.2586816 GLS 0.2560175 0.2631010 IKZF4 0.2468294 0.2189585 NRIP3 0.2446390 0.2170968 SENP1 0.2372014 0.2724868 SLC27A6 0.2321821 0.2218227 SRFBP1 0.2293986 0.2688244 OBFC1 0.2279012 0.2187441 STEAP2 0.2239941 0.2001475
I want to measure if any of the two predicted scores per gene are significantly different from each other, or if the predictions are very similar. I have a biology background so I'm not sure what to start with searching for this, and so sorry if I've asked this question in the wrong place, any help would be appreciated.
I now have 6 score columns in total (all look similar to
Score2) - are there any other statistical tests I can do? Would it be worth doing a t-test?