Transcription factor (TF) proteins play a critical role in the regulation of eukaryote gene expression by sequence-specific binding to genomic locations known as transcription factor binding sites. Here we present the TFBSFootprinter tool which has been created to combine transcription-relevant data from six large empirical datasets: Ensembl, JASPAR, FANTOM5, ENCODE, GTEX, and GTRD to more accurately predict functional sites. A complete analysis integrating all experimental datasets can be performed on genes in the human genome, and a limited analysis can be done on a total of 125 vertebrate species. As a use-case, we have used TFBSFootprinter to study sites of genomic variation between modern humans and Neandertal promoters. We found significant differences in binding affinity for 86 transcription factors, groups of which are both highly expressed, and show correlation of expression, in immune cells and adult and developing neural tissues.