ArticleBMC bioinformatics2019
Ryūtō: network-flow based transcriptome reconstruction.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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Who cites it
11 citing papers in PubMed.
- ComprehensiveNon-coding RNA · 2026Article
- Cov-trans: an efficient algorithm for discontinuous transcript assembly in coronaviruses.BMC genomics · 2024Article
- StringFix: an annotation-guided transcriptome assembler improves the recovery of amino acid sequences from RNA-Seq reads.Genes & genomics · 2023Article
- Phables: from fragmented assemblies to high-quality bacteriophage genomes.Bioinformatics (Oxford, England) · 2023Article
- Phables: from fragmented assemblies to high-quality bacteriophage genomes.bioRxiv : the preprint server for biology · 2023Article
- 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
- Chromosome-level Thlaspi arvense genome provides new tools for translational research and for a newly domesticated cash cover crop of the cooler climates.Plant biotechnology journal · 2022Article
- Deriving Ranges of Optimal Estimated Transcript Expression due to Nonidentifiability.Journal of computational biology : a journal of computational molecular cell biology · 2022Article
- SAUTE: sequence assembly using target enrichment.BMC bioinformatics · 2021Article
- Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
backgroundThe rapid increase in High-throughput sequencing of RNA (RNA-seq) has led to tremendous improvements in the detection and reconstruction of both expressed coding and non-coding RNA transcripts. Yet, the complete and accurate annotation of the complex transcriptional output of not only the human genome has remained elusive. One of the critical bottlenecks in this endeavor is the computational reconstruction of transcript structures, due to high noise levels, technological limits, and other biases in the raw data.
resultsWe introduce several new and improved algorithms in a novel workflow for transcript assembly and quantification. We propose an extension of the common splice graph framework that combines aspects of overlap and bin graphs and makes it possible to efficiently use both multi-splice and paired-end information to the fullest extent. Phasing information of reads is used to further resolve loci. The decomposition of read coverage patterns is modeled as a minimum-cost flow problem to account for the unavoidable non-uniformities of RNA-seq data.
conclusionIts performance compares favorably with state of the art methods on both simulated and real-life datasets. Ryūtō calls 1-4% more true transcripts, while calling 5-35% less false predictions compared to the next best competitor.
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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.