Recent interests in personalized medicine, combined with growing cloud computing resources, have made it possible to analyze large amounts of DNA sequence data in search of links between locations along the genome (single nucleotide polymorphisms, or SNPs) and traits. Some methods use phylogenetic trees, or bifurcating trees that show evolutionary relatedness, to search for SNP-trait relationships. These evolutionary histories differ among genomic locations as an artifact of recombination events along a chromosome. Although work has been done to identify recombination points, even as a component of local phylogeny estimation, researchers lack an intuitive framework for thinking about changes in phylogenies across a chromosome. This challenges interpretations of phylogenetic trees across recombination points. Here, we introduce a phylogenetic derivative to describe the relatedness of neighboring trees along a chromosome. This phylogenetic derivative is a flexible metric that can be also be used assess the prevalence of recombination across a chromosome. The proposed methods are tested and perform well in analyzing both simulated data and real mouse data.