ArticleBioinformatics (Oxford, England)2014
Efficient RNA isoform identification and quantification from RNA-Seq data with network flows.
Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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31 citing papers in PubMed.
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- Integrative analysis of the metabolome and transcriptome reveals the mechanism of polyphenol biosynthesis inFrontiers in plant science · 2024Article
- A safety framework for flow decomposition problems via integer linear programming.Bioinformatics (Oxford, England) · 2023Article
- Long noncoding RNA study: Genome-wide approaches.Genes & diseases · 2023Review
- Alternative splicing in ABA signaling during seed germination.Frontiers in plant science · 2023Review
- Improving RNA Assembly via Safety and Completeness in Flow Decompositions.Journal of computational biology : a journal of computational molecular cell biology · 2022Article
- Efficient Minimum Flow Decomposition via Integer Linear Programming.Journal of computational biology : a journal of computational molecular cell biology · 2022Article
- Deriving Ranges of Optimal Estimated Transcript Expression due to Nonidentifiability.Journal of computational biology : a journal of computational molecular cell biology · 2022Article
- Nanopore long-read RNAseq reveals transcriptional variations in citrus species.Frontiers in plant science · 2022Article
- Jumper enables discontinuous transcript assembly in coronaviruses.Nature communications · 2021Article
- STRONG: metagenomics strain resolution on assembly graphs.Genome biology · 2021Article
- Exact transcript quantification over splice graphs.Algorithms for molecular biology : AMB · 2021Article
- Single-Molecule Long-Read Sequencing Reveals the Diversity of Full-Length Transcripts in Leaves ofInternational journal of molecular sciences · 2019Article
- A multi-sample approach increases the accuracy of transcript assembly.Nature communications · 2019Article
- Ryūtō: network-flow based transcriptome reconstruction.BMC bioinformatics · 2019Article
- Modeling and analysis of RNA-seq data: a review from a statistical perspective.Quantitative biology (Beijing, China) · 2018Article
- Evaluating approaches to find exon chains based on long reads.Briefings in bioinformatics · 2018Article
- MSIQ: JOINT MODELING OF MULTIPLE RNA-SEQ SAMPLES FOR ACCURATE ISOFORM QUANTIFICATION.The annals of applied statistics · 2018Article
- Correction of gene model annotations improves isoform abundance estimates: the example of ketohexokinase (F1000Research · 2018Article
- SparseIso: a novel Bayesian approach to identify alternatively spliced isoforms from RNA-seq data.Bioinformatics (Oxford, England) · 2018Article
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4 authors.
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Abstract
motivationSeveral state-of-the-art methods for isoform identification and quantification are based on [Formula: see text]-regularized regression, such as the Lasso. However, explicitly listing the-possibly exponentially-large set of candidate transcripts is intractable for genes with many exons. For this reason, existing approaches using the [Formula: see text]-penalty are either restricted to genes with few exons or only run the regression algorithm on a small set of preselected isoforms.
resultsWe introduce a new technique called FlipFlop, which can efficiently tackle the sparse estimation problem on the full set of candidate isoforms by using network flow optimization. Our technique removes the need of a preselection step, leading to better isoform identification while keeping a low computational cost. Experiments with synthetic and real RNA-Seq data confirm that our approach is more accurate than alternative methods and one of the fastest available. AVAILABILITY AND IMPLEMENTATION: Source code is freely available as an R package from the Bioconductor Web site (http://www.bioconductor.org/), and more information is available at http://cbio.ensmp.fr/flipflop. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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