A typical gene contains two levels of information: a sequence that encodes a particular protein and a host of other signals that are necessary for the correct expression of the transcript. While much attention has been focused on the effects of sequence variation on the amino acid sequence, variations that disrupt gene processing signals can dramatically impact gene function. A variation that disrupts an exonic splicing enhancer (ESE), for example, could cause exon skipping which would result in the exclusion of an entire exon from the mRNA transcript. RESCUE-ESE, a computational approach used in conjunction with experimental validation, previously identified 238 candidate ESE hexamers in human genes. The RESCUE-ESE method has recently been implemented in three additional species: mouse, zebrafish and pufferfish. Here we describe an online ESE analysis tool (http://genes.mit.edu/burgelab/rescue-ese/) that annotates RESCUE-ESE hexamers in vertebrate exons and can be used to predict splicing phenotypes by identifying sequence changes that disrupt or alter predicted ESEs.