The presented work case interests pairwise sequence alignment algorithms for two analysis cases. The first analysis is SARS-COV2 Omicron in Algerian compared to the neighbor countries using Global and local alignment algorithms, and the second compared coronaviruses from animal sources like Pangolin, Bat, Civet, and Camal, to predict its origin. Of course, with real applications and samples from GISAID, NCBI, and GenBank, and deal with them using the Biopython command line in the Colab platform. The presented work confirms that the local alignment algorithm for the spike region provides better family classification and grouping by matching score sorting. The identity percentage of SARS-COV-2 compared to animal coronaviruses published previously using Simplot software from other authors have wrong values and reviewed in the presented work with the right values using the Biopython library. A high matching score found in bats and pangolins confirms that the origin of SARS-COV-2 is from animal wildlife.