
Abstract Background Alignment-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. Result We 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. Conclusion We 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.
TGIRT-seq, Sequence Analysis, RNA, k-mer, High-Throughput Nucleotide Sequencing, QH426-470, RNA, Transfer, ROC Curve, RNA, Ribosomal, Area Under Curve, Genetics, RNA, RNA-seq, TP248.13-248.65, Algorithms, Biotechnology, Research Article
TGIRT-seq, Sequence Analysis, RNA, k-mer, High-Throughput Nucleotide Sequencing, QH426-470, RNA, Transfer, ROC Curve, RNA, Ribosomal, Area Under Curve, Genetics, RNA, RNA-seq, TP248.13-248.65, Algorithms, Biotechnology, Research Article
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