Evidence map›Paper›PMID 26975657›Full record

ArticleNucleic acids research2016

CLASS2: accurate and efficient splice variant annotation from RNA-seq reads.

Li Song, Sarven Sabunciyan, Liliana Florea

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed
4.0field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

44 citing papers in PubMed, 86 citations in OpenAlex.

  1. Minimum flow decomposition guided by saturating subflows.bioRxiv : the preprint server for biology · 2026
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  4. Benchmarking foundation models for splice site and exon annotation.bioRxiv : the preprint server for biology · 2026
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  10. The genome of Eleocharis vivipara elucidates the genetics of CJournal of integrative plant biology · 2024
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  12. Accurate assembly of multiple RNA-seq samples with Aletsch.Bioinformatics (Oxford, England) · 2024
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  13. Article
  14. PredictingbioRxiv : the preprint server for biology · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Li SongCenter for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA.
Sarven SabunciyanDepartment of Pediatrics, Johns Hopkins School of Medicine, Baltimore, MD 21287, USA.
Liliana FloreaCenter for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA florea@jhu.edu.
Johns Hopkins University · USJohns Hopkins Medicine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Next generation sequencing of cellular RNA is making it possible to characterize genes and alternative splicing in unprecedented detail. However, designing bioinformatics tools to accurately capture splicing variation has proven difficult. Current programs can find major isoforms of a gene but miss lower abundance variants, or are sensitive but imprecise. CLASS2 is a novel open source tool for accurate genome-guided transcriptome assembly from RNA-seq reads based on the model of splice graph. An extension of our program CLASS, CLASS2 jointly optimizes read patterns and the number of supporting reads to score and prioritize transcripts, implemented in a novel, scalable and efficient dynamic programming algorithm. When compared against reference programs, CLASS2 had the best overall accuracy and could detect up to twice as many splicing events with precision similar to the best reference program. Notably, it was the only tool to produce consistently reliable transcript models for a wide range of applications and sequencing strategies, including ribosomal RNA-depleted samples. Lightweight and multi-threaded, CLASS2 requires <3GB RAM and can analyze a 350 million read set within hours, and can be widely applied to transcriptomics studies ranging from clinical RNA sequencing, to alternative splicing analyses, and to the annotation of new genomes.

Indexed as

Alternative SplicingSoftwareAlgorithmsExonsHigh-Throughput Nucleotide SequencingHumansIntronsMolecular Sequence AnnotationPoly APolymerase Chain ReactionProtein IsoformsPrunus persicaReproducibility of ResultsRNARNA, RibosomalPoly AProtein IsoformsRNARNA, Ribosomal

Identifiers

PMID26975657
PMCPMC4889935
OpenAlexW2298558585

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.