Benchmarking tRNA-Seq quantification approaches by realistic tRNA-Seq data simulation identifies two novel approaches with higher accuracy
Smith, T. S.; Monti, M.; Willis, A. E.; Kalmar, L.
Show abstract
Quantification of transfer RNA (tRNA) using illumina sequencing based tRNA-Seq is complicated due to their degree of redundancy and extensive modifications. As such, no tRNA-Seq method has become well established, while various approaches have been proposed to quantify tRNAs from sequencing reads. Here, we use realistic tRNA-Seq simulations to benchmark tRNA-Seq quantification approaches, including two novel approaches. We demonstrate that these novel approaches are consistently the most accurate, using data simulated to mimic five different tRNA-Seq methods. This simulation-based benchmarking also identifies specific shortfalls for each quantification approach and suggests that up to 13% of the variance observed between cell lines in real tRNA-Seq data could be due to systematic differences in quantification accuracy.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.