PAR-CLIP, a CLIP-seq protocol, derives a transcriptome wide set of binding sites for RNA-binding proteins. Even though the protocol uses stringent washing to remove experimental noise, some of it remains. A recent study measured three sets of non-specific RNA backgrounds which are present in several PAR-CLIP datasets. However, a tool to identify the presence of common background in PAR-CLIP datasets is not yet available. In this talk I will introduce a tool that uses this score to identify the amount of common backgrounds present in a PAR-CLIP dataset, and we provide the user the option to use or remove it. My team used the proposed strategy in 30 PAR-CLIP datasets from nine proteins. It is possible to identify the presence of common backgrounds in a dataset and identify differences in datasets for the same protein. This method is the first step in the process of completely removing such backgrounds.