Kevin R Shieh1, Christina Kratschmer2, Keith E Maier3, John M Greally4, Matthew Levy3, Aaron Golden5. 1. Department of Medicine, Maimonides Medical Center, Brooklyn, NY, USA. 2. Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA. 3. Vitrisa Therapeutics, Durham, NC, USA. 4. Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA. 5. School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway, Galway, Ireland.
Abstract
SUMMARY: High-throughput sequencing can enhance the analysis of aptamer libraries generated by the Systematic Evolution of Ligands by EXponential enrichment. Robust analysis of the resulting sequenced rounds is best implemented by determining a ranked consensus of reads following the processing by multiple aptamer detection algorithms. While several such approaches have been developed to this end, their installation and implementation is problematic. We developed AptCompare, a cross-platform program that combines six of the most widely used analytical approaches for the identification of RNA aptamer motifs and uses a simple weighted ranking to order the candidate aptamers, all driven within the same GUI-enabled environment. We demonstrate AptCompare's performance by identifying the top-ranked candidate aptamers from a previously published selection experiment in our laboratory, with follow-up bench assays demonstrating good correspondence between the sequences' rankings and their binding affinities. AVAILABILITY AND IMPLEMENTATION: The source code and pre-built virtual machine images are freely available at https://bitbucket.org/shiehk/aptcompare. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
SUMMARY: High-throughput sequencing can enhance the analysis of aptamer libraries generated by the Systematic Evolution of Ligands by EXponential enrichment. Robust analysis of the resulting sequenced rounds is best implemented by determining a ranked consensus of reads following the processing by multiple aptamer detection algorithms. While several such approaches have been developed to this end, their installation and implementation is problematic. We developed AptCompare, a cross-platform program that combines six of the most widely used analytical approaches for the identification of RNA aptamer motifs and uses a simple weighted ranking to order the candidate aptamers, all driven within the same GUI-enabled environment. We demonstrate AptCompare's performance by identifying the top-ranked candidate aptamers from a previously published selection experiment in our laboratory, with follow-up bench assays demonstrating good correspondence between the sequences' rankings and their binding affinities. AVAILABILITY AND IMPLEMENTATION: The source code and pre-built virtual machine images are freely available at https://bitbucket.org/shiehk/aptcompare. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Skyler T Kramer; Paige R Gruenke; Khalid K Alam; Dong Xu; Donald H Burke Journal: Mol Ther Nucleic Acids Date: 2022-08-24 Impact factor: 10.183