BMC GenomicsBioinformaticsPeer-reviewed journal article
Limitation of alignment-free tools in total RNA-seq quantification
Douglas C. WuiD, Jun YaoiD, Kevin S. Ho, Alan M. LambowitziD, Claus O. WilkeiD
Abstract
BackgroundAlignment-free RNA quantification tools have significantly increased the speed of RNA-seq analysis. However, it is unclear whether these state-of-the-art RNA-seq analysis pipelines can quantify small RNAs as accurately as they do with long RNAs in the context of total RNA quantification.\n\nResultWe comprehensively tested and compared four RNA-seq pipelines on the accuracies of gene quantification and fold-change estimation on a novel total RNA benchmarking dataset, in which small non-coding RNAs are highly represented along with other long RNAs. The four RNA-seq pipelines were of two commonly-used alignment-free pipelines and two variants of alignment-based pipelines. We found that all pipelines showed high accuracies for quantifying the expressions of long and highly-abundant genes. However, alignment-free pipelines showed systematically poorer performances in quantifying lowly-abundant and small RNAs.\n\nConclusionWe have shown that alignment-free and traditional alignment-based quantification methods performed similarly for common gene targets, such as protein-coding genes. However, we identified a potential pitfall in analyzing and quantifying lowly-expressed genes and small RNAs with alignment-free pipelines, especially when these small RNAs contain mutations.
- assay: bulk RNA-seq
- research focus: benchmarking
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: variant calling
- approach: statistical model
- Citations
- 83
- FWCI
- 4.45
- Field percentile
- top 4%
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