AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers

Dario Ruiz-Ciancio; Suresh Veeramani; Eric Embree; Chris Ortman; Kristina W Thiel; William H Thiel

doi:10.1101/2023.11.13.566453

Back

AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers

Preprint

Open access

AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers

Dario Ruiz-Ciancio, Suresh Veeramani, Eric Embree, Chris Ortman, Kristina W Thiel and William H Thiel

bioRxiv : the preprint server for biology

11/15/2023

DOI: 10.1101/2023.11.13.566453

PMCID: PMC10680646

PMID: 38014343

Files and links (1)

url

https://doi.org/10.1101/2023.11.13.566453View

Published (Version of record)This preprint has not been evaluated by subject experts through peer review. Preprints may undergo extensive changes and/or become peer-reviewed journal articles. Open Access

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.

Details

Title: Subtitle: AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers
Creators: Dario Ruiz-Ciancio - Cancer Genome Engineering Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona 08035, Spain
Suresh Veeramani - Holden Comprehensive Cancer Center, University of Iowa, Iowa City, IA, 52242, USA
Eric Embree - Carver College of Medicine, University of Iowa, Iowa City, IA 52242, USA
Chris Ortman - Institute for Clinical and Translational Science, University of Iowa, Iowa City, IA 52242, USA
Kristina W Thiel - University of Iowa
William H Thiel - Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA
Resource Type: Preprint
Publication Details: bioRxiv : the preprint server for biology
DOI: 10.1101/2023.11.13.566453
PMID: 38014343
PMCID: PMC10680646
Publisher: United States
Grant note: R01 HL139581 / NHLBI NIH HHS K22 CA263783 / NCI NIH HHS
Language: English
Date posted: 11/15/2023
Academic Unit: Hematology, Oncology, and Blood & Marrow Transplantation; Cardiovascular Medicine; Obstetrics and Gynecology; Internal Medicine
Record Identifier: 9984528097502771

Metrics

20 Record Views