Thanks in advance for even read this.
I am new in bioinformatic (3-4 month with rudimentary R programming knowledge). I need some constructive comment before I embark on this stuff. I am writing my PhD thesis (due in 6 month). The part that I write below should be the 1st half of my thesis (the 2nd half will be metabolites data from multiple gene edited mice).
Let say, I have 12 genes of interest ("A - M") which might be related to certain diseases or "X" biological pathway. Our Department already have "X" pathway metabolites data from gene edited mice (KO/KD) from all these 12 genes.
My main/general objective is to identify which of these 12 genes is the most important a) amongst themselves and b) in system biology in general.
To answer this I thought Meta-Analyses of Gene Expression Data might be a good idea to answer a by comparing the 12 genes expression pattern and in various associated disease model to answer b.
Here is the main Question How to explain and study pattern?. Right now, my plan is, using PRISMA Systematic Review guide to filter Mice MicroArray Dataset (because our metabolites data is from mice and I only kinda adept using R to manipulate MicroArray dataset), and then conduct Meta-Analyses of the datasets using P-value combination, Fisher's Method.
But then after that I am lost. What should I do next?