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BEERS2: RNA-Seq simulation through high fidelity in silico modeling

Simulation of RNA-seq reads is critical in the assessment, comparison, benchmarking, and development of bioinformatics tools. Yet the field of RNA-seq simulators has progressed little in the last decade. To address this need we have developed BEERS2, which combines a flexible and highly configurable...

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Autores principales: Brooks, Thomas G., Lahens, Nicholas F., Mrčela, Antonijo, Sarantopoulou, Dimitra, Nayak, Soumyashant, Naik, Amruta, Sengupta, Shaon, Choi, Peter S., Grant, Gregory R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168222/
https://www.ncbi.nlm.nih.gov/pubmed/37162982
http://dx.doi.org/10.1101/2023.04.21.537847
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author Brooks, Thomas G.
Lahens, Nicholas F.
Mrčela, Antonijo
Sarantopoulou, Dimitra
Nayak, Soumyashant
Naik, Amruta
Sengupta, Shaon
Choi, Peter S.
Grant, Gregory R.
author_facet Brooks, Thomas G.
Lahens, Nicholas F.
Mrčela, Antonijo
Sarantopoulou, Dimitra
Nayak, Soumyashant
Naik, Amruta
Sengupta, Shaon
Choi, Peter S.
Grant, Gregory R.
author_sort Brooks, Thomas G.
collection PubMed
description Simulation of RNA-seq reads is critical in the assessment, comparison, benchmarking, and development of bioinformatics tools. Yet the field of RNA-seq simulators has progressed little in the last decade. To address this need we have developed BEERS2, which combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline. BEERS2 takes input transcripts (typically fully-length mRNA transcripts with polyA tails) from either customizable input or from CAMPAREE simulated RNA samples. It produces realistic reads of these transcripts as FASTQ, SAM, or BAM formats with the SAM or BAM formats containing the true alignment to the reference genome. It also produces true transcript-level quantification values. BEERS2 combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline and is designed to include the effects of polyA selection and RiboZero for ribosomal depletion, hexamer priming sequence biases, GC-content biases in PCR amplification, barcode read errors, and errors during PCR amplification. These characteristics combine to make BEERS2 the most complete simulation of RNA-seq to date. Finally, we demonstrate the use of BEERS2 by measuring the effect of several settings on the popular Salmon pseudoalignment algorithm.
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spelling pubmed-101682222023-05-10 BEERS2: RNA-Seq simulation through high fidelity in silico modeling Brooks, Thomas G. Lahens, Nicholas F. Mrčela, Antonijo Sarantopoulou, Dimitra Nayak, Soumyashant Naik, Amruta Sengupta, Shaon Choi, Peter S. Grant, Gregory R. bioRxiv Article Simulation of RNA-seq reads is critical in the assessment, comparison, benchmarking, and development of bioinformatics tools. Yet the field of RNA-seq simulators has progressed little in the last decade. To address this need we have developed BEERS2, which combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline. BEERS2 takes input transcripts (typically fully-length mRNA transcripts with polyA tails) from either customizable input or from CAMPAREE simulated RNA samples. It produces realistic reads of these transcripts as FASTQ, SAM, or BAM formats with the SAM or BAM formats containing the true alignment to the reference genome. It also produces true transcript-level quantification values. BEERS2 combines a flexible and highly configurable design with detailed simulation of the entire library preparation and sequencing pipeline and is designed to include the effects of polyA selection and RiboZero for ribosomal depletion, hexamer priming sequence biases, GC-content biases in PCR amplification, barcode read errors, and errors during PCR amplification. These characteristics combine to make BEERS2 the most complete simulation of RNA-seq to date. Finally, we demonstrate the use of BEERS2 by measuring the effect of several settings on the popular Salmon pseudoalignment algorithm. Cold Spring Harbor Laboratory 2023-04-24 /pmc/articles/PMC10168222/ /pubmed/37162982 http://dx.doi.org/10.1101/2023.04.21.537847 Text en https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Brooks, Thomas G.
Lahens, Nicholas F.
Mrčela, Antonijo
Sarantopoulou, Dimitra
Nayak, Soumyashant
Naik, Amruta
Sengupta, Shaon
Choi, Peter S.
Grant, Gregory R.
BEERS2: RNA-Seq simulation through high fidelity in silico modeling
title BEERS2: RNA-Seq simulation through high fidelity in silico modeling
title_full BEERS2: RNA-Seq simulation through high fidelity in silico modeling
title_fullStr BEERS2: RNA-Seq simulation through high fidelity in silico modeling
title_full_unstemmed BEERS2: RNA-Seq simulation through high fidelity in silico modeling
title_short BEERS2: RNA-Seq simulation through high fidelity in silico modeling
title_sort beers2: rna-seq simulation through high fidelity in silico modeling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168222/
https://www.ncbi.nlm.nih.gov/pubmed/37162982
http://dx.doi.org/10.1101/2023.04.21.537847
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