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. 2017 Jun 1;7:2593. doi: 10.1038/s41598-017-02464-y

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© The Author(s) 2017

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Outline of the UROPA algorithm. (1) For each peak all queries are consecutively checked for features satisfying various optional criteria. (2) The resulting candidate features are ranked for each query based on the distance of the peak center to the feature anchor(s) of interest (e.g. start, end, center of the feature). (3) All candidate features resulting from any query are stored in the”all hits” table. (4) The best candidate feature for each query is stored in the “best hits” table. (5) Only the one best feature among all queries is stored in the “final hits” table. This step can optionally include prioritization of queries to ensure a desired precedence (e.g. prefer protein_coding genes even if they are located farther away from the peak). These three output files cover various granularities considering the desired outcome.