Supporting data for "Using synthetic RNA to benchmark poly(A) length inference from direct RNA sequencing."
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Reames B
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Yang X
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https://doi.org/10.5524/102736
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BoostNano-master
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Chang JJ
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Coin LJM
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Teng H
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Corbin V
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boostnano_no_dorado_R1_tails.csv
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description: PolyA tail lengths as found by Boostnano for R1 sequins which were filtered out by Dorado but kept by Boostnano; underlying data for figure 3
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readme_102736.txt
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Supporting data for "Using synthetic RNA to benchmark poly(A) length inference from direct RNA sequencing."
author: Reames B
author: Yang X
author: Chang JJ
author: Coin LJM
author: Teng H
author: Corbin V
citation: https://doi.org/10.5524/100425
content size: 8266
date created: 2025-07-29 00:00:00
date modified: 2025-10-16 11:11:58.719757+00:00
date published: 2025-07-29 00:00:00
description: 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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funder: National Health and Medical Research Council
has part: boostnano_no_dorado_R1_tails.csv
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keywords: oxford nanopore technologies, poly(a) tail, estimation, segmentation, direct rna sequencing
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cite-as: Chang JJ, Coin LJM, Teng H, Corbin V, Yang X, and Reames B. "Supporting data for "Using synthetic RNA to benchmark poly(A) length inference from direct RNA sequencing."." ROHub. Jul 29 ,2025. https://w3id.org/ro-id/3543b082-9077-492e-a4c7-a3b7c8bb39e8.

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