A replicable and modular benchmark for long-read transcript quantification methods

Abstract

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