GenFooT: Genomic Footprint of mitochondrial sequence for Taxonomy classification

The annotation of the sequences plays an important role in the taxonomic characteristics, medical research, phylogenetic studies, etc. Most of the existing classification techniques focused on some distinct group of organisms and considered the specific fragments of genome sequence, such as particular gene or RNAs. Here, we introduce a novel representation of genome sequence in a 2D coordinate space and extract features from the 2D representation. These features are used to classify a set of species into different taxonomy ranks. We experiment our proposed method, GenFooT, on nine different datasets of genomic sequences of various organisms. Our experimental results indicate improved classification performance of the proposed features with both Linear discriminant analysis and Logistic regression classifiers. This study demonstrates that our proposed alignment-free method, GenFooT, is fast, accurate, and can be applied to the large-scale genomics studies.