Gene expression analysis is critical to find out important genes associated with diseases. Computational methods such as differential expression analysis and various gene network analyses are used to find such genes which are expressed differently in a diseased sample compared to a control sample (sample without the disease). Such studies have helped understand the genetic causes of various critical diseases including neuro-psychiatric disorders. We have focused our work on functionally related genes associated with Schizophrenia as there is still much to be unearthed about the genetic causes that leads to this disorder. In this paper, we have used a combination of different computational methods to analyze bulk-RNA Seq data for schizophrenia to find pairs of functionally related genes that contribute to its occurrence. We are able to find pairs of genes that have been associated with the target disease along with other pairs which are yet to be established as important genes for the disease pathogenesis.