Transcriptional enhancers are DNA regulatory elements that are bound by 
transcription factors and act to positively regulate the expression of nearby or 
distally located target genes. Enhancers have many features that have been 
discovered using genomic analyses. Recent studies have shown that active 
enhancers recruit RNA polymerase II (Pol II) and are transcribed, producing 
enhancer RNAs (eRNAs). GRO-seq, a method for identifying the location and 
orientation of all actively transcribing RNA polymerases across the genome, is a 
powerful approach for monitoring nascent enhancer transcription. Furthermore, 
the unique pattern of enhancer transcription can be used to identify enhancers 
in the absence of any information about the underlying transcription factors. 
Here, we describe the computational approaches required to identify and analyze 
active enhancers using GRO-seq data, including data pre-processing, alignment, 
and transcript calling. In addition, we describe protocols and computational 
pipelines for mining GRO-seq data to identify active enhancers, as well as known 
transcription factor binding sites that are transcribed. Furthermore, we discuss 
approaches for integrating GRO-seq-based enhancer data with other genomic data, 
including target gene expression and function. Finally, we describe molecular 
biology assays that can be used to confirm and explore further the function of 
enhancers that have been identified using genomic assays. Together, these 
approaches should allow the user to identify and explore the features and 
biological functions of new cell type-specific enhancers.