An integrated statistical comparative analysis between variant genetic datasets of Mus musculus

Comparative genomic analysis between variant datasets of same specie is considered to be vital to discover the degree of relevancy in them. This analysis helps in the categorisation of diversity of features in species. An immense need was felt to build sophisticated tools for efficient and robust comparative analysis. The accuracy of methodologies is directly proportional to sensitivity involved in comparing datasets for optimality. This paper is a depiction of an effort for the discovery of variant features between genetic datasets of Mus musculus. The approach described is demonstrated phase-wise with the inclusion of specific filters at each stage. At first instance, cleansing filter refines the datasets. Further series of filters depict the layered process for comprehensive comparative analysis. Numerical results have been evaluated. The protein translation phase has been introduced with conceptual demonstration of codon composition phenomenon. Characteristics of density, nucleotide strengths and codon composition better reflect the relevancy in genetic datasets of Mus musculus