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bioRxiv · 10.1101/2024.10.25.620206

Using synthetic RNA to benchmark poly(A) length inference from direct RNA sequencing.

Chang, J. J.-Y.·Yang, X.·Teng, H.·Reames, B.·Corbin, V.·Coin, L. J. M.
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Abstract

Polyadenylation is a dynamic process which is important in cellular physiology. Oxford Nanopore Technologies direct RNA-sequencing provides a strategy for sequencing the full-length RNA molecule and analysis of the transcriptome and epi-transcriptome. There are currently several tools available for poly(A) tail-length estimation, including well-established tools such as tailfindr and nanopolish, as well as two more recent deep learning models: Dorado and BoostNano. However, there has been limited benchmarking of the accuracy of these tools against gold-standard datasets. In this paper we evaluate four poly(A) estimation tools using synthetic RNA standards (Sequins), which have known poly(A) tail-lengths and provide a valuable approach to measuring the accuracy of poly(A) tail-length estimation. All four tools generate mean tail-length estimates which lie within 12% of the correct value. Overall, Dorado is recommended as the preferred approach due to its relatively fast run times, low coefficient of variation and ease of use with integration with base-calling.

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Chang, J. J.-Y., Yang, X., Teng, H., Reames, B., Corbin, V., Coin, L. J. M.. 2024-10-25. Using synthetic RNA to benchmark poly(A) length inference from direct RNA sequencing.. https://doi.org/10.1101/2024.10.25.620206

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