ArticleNucleic acids research2012
Modelling and simulating generic RNA-Seq experiments with the flux simulator.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 154 papers.
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Who cites it
154 citing papers in PubMed, 311 citations in OpenAlex.
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- Improved reconstruction of transcripts and coding sequences from RNA-seq data.Nucleic acids research · 2026Article
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- Challenges and best practices in omics benchmarking.Nature reviews. Genetics · 2024Review
- BEERS2: RNA-Seq simulation through high fidelity in silico modeling.Briefings in bioinformatics · 2024Article
- StringFix: an annotation-guided transcriptome assembler improves the recovery of amino acid sequences from RNA-Seq reads.Genes & genomics · 2023Article
- TRS: a method for determining transcript termini from RNAtag-seq sequencing data.Nature communications · 2023Article
- A safety framework for flow decomposition problems via integer linear programming.Bioinformatics (Oxford, England) · 2023Article
- OnACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2023Article
- Counting pseudoalignments to novel splicing events.Bioinformatics (Oxford, England) · 2023Article
- REPAC: analysis of alternative polyadenylation from RNA-sequencing data.Genome biology · 2023Article
- Improving RNA Assembly via Safety and Completeness in Flow Decompositions.Journal of computational biology : a journal of computational molecular cell biology · 2022Article
94 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
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-throughput sequencing of cDNA libraries constructed from cellular RNA complements (RNA-Seq) naturally provides a digital quantitative measurement for every expressed RNA molecule. Nature, impact and mutual interference of biases in different experimental setups are, however, still poorly understood-mostly due to the lack of data from intermediate protocol steps. We analysed multiple RNA-Seq experiments, involving different sample preparation protocols and sequencing platforms: we broke them down into their common--and currently indispensable--technical components (reverse transcription, fragmentation, adapter ligation, PCR amplification, gel segregation and sequencing), investigating how such different steps influence abundance and distribution of the sequenced reads. For each of those steps, we developed universally applicable models, which can be parameterised by empirical attributes of any experimental protocol. Our models are implemented in a computer simulation pipeline called the Flux Simulator, and we show that read distributions generated by different combinations of these models reproduce well corresponding evidence obtained from the corresponding experimental setups. We further demonstrate that our in silico RNA-Seq provides insights about hidden precursors that determine the final configuration of reads along gene bodies; enhancing or compensatory effects that explain apparently controversial observations can be observed. Moreover, our simulations identify hitherto unreported sources of systematic bias from RNA hydrolysis, a fragmentation technique currently employed by most RNA-Seq protocols.
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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.