Paper Title
Identification of Differentially Expressed Genes in Intellectual Disability through Meta-Analysis of RNA-SEQ Data

Abstract
Abstract - The identification of differentially expressed genes (DEGs) can provide significant information regarding the pathology and mechanism of the disease. The identification of DEGs has led to relevant research in pharmaceutical and clinical industry. These DEGs can act as a therapeutic target, potent biomarker, or gene signature leading to the early diagnosis of the disease. Intellectual disability is a neurodevelopmental disorder, that is, it affects the mental growth of the child at the fetal stage. The timely diagnosis of this disease can improve the quality of living. In the current study, meta-analysis approach was applied to identify the differentially expressed genes in intellectual disability disorder. Data from 6 different intellectual disability datasets from the GEO database (GSE98476, GSE74263, GSE77742, PRJEB21964, GSE108887, GSE90682) of NCBI were taken and subjected to quality check, trimming, and alignment using fastqc, trimmomatic and Hisat2. After pre-processing, the raw gene count file was made using feature Counts for the differential analysis. The differentially expression of genes were evaluated using the DESeq2 statistical package of R. The genes which had the adjusted p-value less than 0.05 and log2foldchange greater than 0 were considered as the upregulated and significantly expressed genes. Through metagenomics analysis 9 upregulated genes were obtained which are, MTRNR2L1, PCDHGB5, RN7SL181P, TANC1, NAV3, ZCCHC24, IGLV3-19, DPYSL3, and IGKV1-16. These genes can be a key node involved in the development and progression of intellectual disability disorder that may facilitate early diagnosis of the disease. Keywords - Intellectual Disability, Deseq2, Biomarker, Neuro developmental Disorder, Meta-Analysis, Differential Gene Expression Analysis.