ArticleGenome biology2015
Comparative assessment of methods for the computational inference of transcript isoform abundance from RNA-seq data.
Article in Genome biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers.
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.
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.
Who cites it
83 citing papers in PubMed, 154 citations in OpenAlex.
- Benchmarking RNA-seq with the Quartet and MAQC reference materials to establish best practices for accurate alternative splicing analysis.Nature communications · 2026Article
- Carbohydrate-active enzymes of soil prophages enhance global carbon cycling potential.Nature communications · 2026Article
- Functional profiling of somatostatin receptors identifies somatostatin receptor subtype 2 as a vulnerability in Succinate Dehydrogenase SDHB-deficient pheochromocytomas and paragangliomas.Molecular biomedicine · 2026Article
- Advances in Mass Spectrometry Instrumentation and Methodology for Analysis of Alternative Protein Isoforms.Journal of mass spectrometry : JMS · 2026Review
- Eukan: a fully automated nuclear genome annotation pipeline for less studied and divergent eukaryotes.NAR genomics and bioinformatics · 2026Article
- Long-Read Sequencing Reveals Cell- and State-Specific Alternative Splicing in 293T and A549 Cell Transcriptomes.International journal of molecular sciences · 2026Article
- HBMC bioinformatics · 2025Article
- Comprehensive assessment of mRNA isoform detection methods for long-read sequencing data.Nature communications · 2024Article
- High-throughput RNA isoform sequencing using programmed cDNA concatenation.Nature biotechnology · 2024Article
- How tool combinations in different pipeline versions affect the outcome in RNA-seq analysis.NAR genomics and bioinformatics · 2024Article
- Full-length isoform concatenation sequencing to resolve cancer transcriptome complexity.BMC genomics · 2024Article
- IsoTools: a flexible workflow for long-read transcriptome sequencing analysis.Bioinformatics (Oxford, England) · 2023Article
- Bridging the splicing gap in human genetics with long-read RNA sequencing: finding the protein isoform drivers of disease.Human molecular genetics · 2022Review
- Exploring differential exon usage via short- and long-read RNA sequencing strategies.Open biology · 2022Article
- The Carbon Footprint of Bioinformatics.Molecular biology and evolution · 2022Article
- Experimental Design for Time-Series RNA-Seq Analysis of Gene Expression and Alternative Splicing.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Exon-level estimates improve the detection of differentially expressed genes in RNA-seq studies.RNA biology · 2021Article
- Article
- A community challenge to evaluate RNA-seq, fusion detection, and isoform quantification methods for cancer discovery.Cell systems · 2021Article
- Nanopore sequencing reveals endogenous NMD-targeted isoforms in human cells.Genome biology · 2021Article
23 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUnderstanding the regulation of gene expression, including transcription start site usage, alternative splicing, and polyadenylation, requires accurate quantification of expression levels down to the level of individual transcript isoforms. To comparatively evaluate the accuracy of the many methods that have been proposed for estimating transcript isoform abundance from RNA sequencing data, we have used both synthetic data as well as an independent experimental method for quantifying the abundance of transcript ends at the genome-wide level.
resultsWe found that many tools have good accuracy and yield better estimates of gene-level expression compared to commonly used count-based approaches, but they vary widely in memory and runtime requirements. Nucleotide composition and intron/exon structure have comparatively little influence on the accuracy of expression estimates, which correlates most strongly with transcript/gene expression levels. To facilitate the reproduction and further extension of our study, we provide datasets, source code, and an online analysis tool on a companion website, where developers can upload expression estimates obtained with their own tool to compare them to those inferred by the methods assessed here.
conclusionsAs many methods for quantifying isoform abundance with comparable accuracy are available, a user's choice will likely be determined by factors such as the memory and runtime requirements, as well as the availability of methods for downstream analyses. Sequencing-based methods to quantify the abundance of specific transcript regions could complement validation schemes based on synthetic data and quantitative PCR in future or ongoing assessments of RNA-seq analysis methods.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.