AptCompare: Optimized de novo motif discovery of RNA aptamers via HTS-SELEX

Kevin R. Shieh, Christina Kratschmer, Keith E. Maier, John M. Greally, Matthew Levy, Aaron Golden

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)2905-2906
Number of pages2
JournalBioinformatics
Volume36
Issue number9
DOIs
StatePublished - May 1 2020

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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