ArticleStatistical science : a review journal of the Institute of Mathematical Statistics2011
Statistical Modeling of RNA-Seq Data.
Article in Statistical science : a review journal of the Institute of Mathematical Statistics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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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.
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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.
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Who cites it
41 citing papers in PubMed.
- Molecular responses in abdominal subcutaneous adipose tissue after a session of endurance exercise: effects of exercise intensity.The Journal of physiology · 2025Article
- Acute session of three endurance exercise intensities alters subcutaneous adipose tissue transcriptome in regular exercisers.bioRxiv : the preprint server for biology · 2025Article
- Statistical modeling of immunoprecipitation efficiency of MeRIP-seq data enabled accurate detection and quantification of epitranscriptome.Computational and structural biotechnology journal · 2025Article
- Article
- SPLASH: a statistical, reference-free genomic algorithm unifies biological discovery.bioRxiv : the preprint server for biology · 2023Article
- Monitoring and modelling the dynamics of the cellular glycolysis pathway: A review and future perspectives.Molecular metabolism · 2022Review
- A model for isoform-level differential expression analysis using RNA-seq data without pre-specifying isoform structure.PloS one · 2022Article
- miRbiom: Machine-learning on Bayesian causal nets of RBP-miRNA interactions successfully predicts miRNA profiles.PloS one · 2021Article
- Article
- The Effect of Hybridization on Dosage Compensation in Member Species of the Anopheles gambiae Species Complex.Genome biology and evolution · 2018Article
- Bayesian Analysis of RNA-Seq Data Using a Family of Negative Binomial Models.Bayesian analysis · 2018Article
- Strawberry: Fast and accurate genome-guided transcript reconstruction and quantification from RNA-Seq.PLoS computational biology · 2017Article
- Improved data-driven likelihood factorizations for transcript abundance estimation.Bioinformatics (Oxford, England) · 2017Article
- Salmon provides fast and bias-aware quantification of transcript expression.Nature methods · 2017Article
- Statistical inference for time course RNA-Seq data using a negative binomial mixed-effect model.BMC bioinformatics · 2016Article
- The genetic regulatory signature of type 2 diabetes in human skeletal muscle.Nature communications · 2016Article
- Circular RNAs: analysis, expression and potential functions.Development (Cambridge, England) · 2016Review
- Human Proteomic Variation Revealed by Combining RNA-Seq Proteogenomics and Global Post-Translational Modification (G-PTM) Search Strategy.Journal of proteome research · 2016Article
- A Rejection Principle for Sequential Tests of Multiple Hypotheses Controlling Familywise Error Rates.Scandinavian journal of statistics, theory and applications · 2016Article
- Designing alternative splicing RNA-seq studies. Beyond generic guidelines.Bioinformatics (Oxford, England) · 2015Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Recently, ultra high-throughput sequencing of RNA (RNA-Seq) has been developed as an approach for analysis of gene expression. By obtaining tens or even hundreds of millions of reads of transcribed sequences, an RNA-Seq experiment can offer a comprehensive survey of the population of genes (transcripts) in any sample of interest. This paper introduces a statistical model for estimating isoform abundance from RNA-Seq data and is flexible enough to accommodate both single end and paired end RNA-Seq data and sampling bias along the length of the transcript. Based on the derivation of minimal sufficient statistics for the model, a computationally feasible implementation of the maximum likelihood estimator of the model is provided. Further, it is shown that using paired end RNA-Seq provides more accurate isoform abundance estimates than single end sequencing at fixed sequencing depth. Simulation studies are also given.
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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.