Evidence map›Paper›PMID 42531061›Full record

ArticleBriefings in bioinformatics2026

Efficient reconstruction of full-length RNA isoforms using ISAtools and large-scale PacBio circular consensus sequencing data.

Hu Chen, Yu-Chen Zhang, Qi Dai, Zhuo-Xing Shi

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Hu ChenCollege of Life Science and Medicine, Zhejiang Sci-Tech University, Second Street 928, Qiantang District, Hangzhou 310018, China.ORCID 0009-0007-0540-7036
Yu-Chen ZhangCollege of Life Science and Medicine, Zhejiang Sci-Tech University, Second Street 928, Qiantang District, Hangzhou 310018, China.
Qi DaiCollege of Life Science and Medicine, Zhejiang Sci-Tech University, Second Street 928, Qiantang District, Hangzhou 310018, China.
Zhuo-Xing ShiState Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, No. 7 Jinsui Road, Tianhe District, Guangzhou 510060, China.

Funding

National Key Research and Development Program of China 2023YFF1205000National Natural Science Foundation of China 42107148National Natural Science Foundation of China 62572442
6 · The paper itself

Abstract

Accurate reconstruction and quantification of full-length RNA isoforms remain challenging in long-read RNA sequencing due to sequencing artifacts, complex splicing, and incomplete annotations. Although Pacific Biosciences circular consensus sequencing (PacBio CCS) provides high-fidelity long reads, scalable and annotation-flexible analysis frameworks remain limited. Here, we present ISAtools, an efficient framework specifically designed for PacBio CCS data. ISAtools introduces a splice site chain representation that unifies read alignments and transcript annotations into a compact format for scalable isoform reconstruction. It further integrates unsupervised density-based clustering for transcription start and end site detection and a truncation-aware quantification strategy. Benchmarking on simulated, SIRV spike-in controls, and biological datasets shows that ISAtools accurately reconstructs both annotated and novel isoforms with reliable splice structures and transcript boundaries while maintaining high computational efficiency. ISAtools processes up to 80 million reads in ~21 min using ~6 GB memory and scales to nearly 1 billion reads in under 4 h with ~8 GB memory, supporting large-scale PacBio Iso-Seq studies.

Indexed as

RNA IsoformsSequence Analysis, RNASoftwareAlgorithmsComputational BiologyHigh-Throughput Nucleotide SequencingHumansRNA Splice SitesRNA IsoformsRNA Splice Sitesisoform reconstructionlong-read RNA sequencingPacBio CCSsplice site chaintranscript boundary detection

Identifiers

PMID42531061
PMCPMC13435227

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.