A Parallel Computing Approach to Gene Expression and Phenotype Correlation for Identifying Retinitis Pigmentosa Modifiers in Drosophila

As a genetic eye disorder, retinitis pigmentosa (RP) has been focus of researchers to find diagnosis through either genome-wide association (GWA) or RNAseq analysis. In fact, GWA and are considered two complementary approaches gaining more comprehensive understanding the genetics different diseases. However, analysis can provide information about specific mechanisms underlying disease potential targets for therapy. This research proposes new approach differential gene expression (DGE) analysis, which is heart core-analysis phase in any study. Based on Drosophila Genetic Reference Panel (DGRP), dataset computationally analyzed light eye-size phenotypes. We utilized foreach doParallel R packages run code multicore machine reduce running time original algorithm, exhibited an exponential complexity. Experimental results showed outstanding performance, reducing by 95% while using 32 processes. addition, candidate modifier genes RP were identified increasing scope considering datasets that represent phenotype models.