Molecular Therapy — Nucleic AcidsBioinformaticsPeer-reviewed journal article
AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers
Dario Ruiz-CiancioiD, Suresh VeeramaniiD, Rahul SinghiD, Eric Embree, Chris OrtmaniD, Kristina W. ThieliD, William H. ThieliD
Abstract
Aptamers are short single-stranded DNA or RNA molecules with high affinity and specificity for targets and are generated using the iterative Systematic Evolution of Ligands by EXponential enrichment (SELEX) process. Next-generation sequencing (NGS) revolutionized aptamer selections by allowing a more comprehensive analysis of SELEX-enriched aptamers as compared to Sanger sequencing. The current challenge with aptamer NGS datasets is identifying a diverse cohort of candidate aptamers with the highest likelihood of successful experimental validation. Herein we present AptamerRunner, an aptamer clustering algorithm that generates visual networks of aptamers that are related by sequence and/or structure. These networks can then be overlayed with ranking data, such as fold enrichment or data from scoring algorithms. The ability to visually integrate data using AptamerRunner represents a significant advancement over existing clustering tools by providing a natural context to depict groups of aptamers from which ranked or scored candidates can be chosen for experimental validation. The inherent flexibility, user-friendly design, and prospects for future enhancements with AptamerRunner has broad-reaching implications for aptamer researchers across a wide range of disciplines. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=99 SRC="FIGDIR/small/566453v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@f63049org.highwire.dtl.DTLVardef@dc26dcorg.highwire.dtl.DTLVardef@17b7381org.highwire.dtl.DTLVardef@1dc39af_HPS_FORMAT_FIGEXP M_FIG C_FIG
- Citations
- 16
- FWCI
- 2.18
- Field percentile
- top 11%
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