A replicable and modular benchmark for long-read transcript quantification methods DOI Creative Commons
Zahra Zare, Noor Singh, Rob Patro

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Июль 31, 2024

Abstract We provide a replicable benchmark for long-read transcript quantification, and evaluate the performance of some recently-introduced tools on several synthetic RNA-seq datasets. This is designed to allow results be easily replicated by other researchers, structure underlying Snakemake workflow modular make addition new or data sets relatively easy. In analyzing previously assessed simulations, we find discrepancies with recently-published results. also demonstrate that robustness certain approaches hinge critically quality “cleanness” simulated data. Availability The scripts are available at https://github.com/COMBINE-lab/lr_quant_benchmarks , used as input benchmarks (reference sequences, annotations, reads) https://doi.org/10.5281/zenodo.13130623 .

Язык: Английский

A replicable and modular benchmark for long-read transcript quantification methods DOI Creative Commons
Zahra Zare, Noor Singh, Rob Patro

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Июль 31, 2024

Abstract We provide a replicable benchmark for long-read transcript quantification, and evaluate the performance of some recently-introduced tools on several synthetic RNA-seq datasets. This is designed to allow results be easily replicated by other researchers, structure underlying Snakemake workflow modular make addition new or data sets relatively easy. In analyzing previously assessed simulations, we find discrepancies with recently-published results. also demonstrate that robustness certain approaches hinge critically quality “cleanness” simulated data. Availability The scripts are available at https://github.com/COMBINE-lab/lr_quant_benchmarks , used as input benchmarks (reference sequences, annotations, reads) https://doi.org/10.5281/zenodo.13130623 .

Язык: Английский

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