Comparative statistics for DNA and protein sequences: Single sequence analysis

Abstract

Four categories of data representations are used to help interpret structures and similarities of nucleic acid and protein sequences. Statistical significance of the observed relationships revealed by these representations are assessed by a hierarchy of permutation procedures and by comparisons with theoretical random models. Applications are presented for various DNA sequences including papovaviruses, Epstein-Barr virus, mitochondrial genomes, and several globin and immunoglobulin genes.