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APV-Sankey: A Comprehensive Toolbox for Aptamer Screening and Visualization

Zhang, Y.; Wang, Y.; Gao, Y.; Hu, K.; Gong, H.; Jia, H.; Zhang, X.; Lou, X.

2025-02-15 bioinformatics
10.1101/2025.02.11.637585 bioRxiv
Show abstract

Aptamers, short single-stranded DNA or RNA molecules, have gained prominence as molecular recognition elements in diagnostics and therapeutics. Screening high-performance aptamers from SELEX process is tough due to limited library diversity, PCR bias, and low library enrichment efficiency. The enriched highest frequency sequences often do not have the highest affinity or specificity. Thus, we developed APV-Sankey, a novel and versatile toolbox designed for the rapid aptamer screening and visualization of the enrichment process. Its key feature is the innovative use of Sankey charts for interactive and informative visualizations. These charts facilitate tracing the evolution of K-mers (K-mer is just a sequence of k characters in a string) across SELEX rounds, aiding in the identification and selection of high-affinity sequences containing K-mers while excluding high-frequency sequences without affinity. Besides integrating essential functions for aptamer analysis, we also developed advanced methods including K-mer concatenation and K-mer evolution, combined with Sankey chart visualizations. Using this toolbox to analyze experimentally screened sequences, we successfully identified high-performance candidate aptamers of rapamycin and thrombin.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
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Top 9%
4.1%
50% of probability mass above
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Top 1.0%
2.8%
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Top 3%
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11
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2.1%
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.