Abstract: Epidermal growth factor receptor (EGFR) is a transmembrane receptor which consists of an extracellular ligand-binding domain, a transmembrane domain and an intracellular tyrosine kinase domain. Several mutations have been resulted due to multiple factors. Patients with EFGR mutations are particularly responsive to the small molecule TKIs. Although it was observed that, the frequency of EGFR mutation is significantly higher in patients who have never smoked. Testing for mutations in EGFR is therefore an important step in the treatment-decision pathway. Several different testing methods offer a more sensitive alternative to direct sequencing for the detection of common EGFR mutations. This study involves, analysis and comparison of EFGR gene variants by using computational biology tools.