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Single Read and Paired End mRNA-Seq Illumina Libraries from 10 Nanograms Total RNA
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Limitations of alignment-free tools in total RNA-seq quantification.

Douglas C Wu1,2, Jun Yao1,2, Kevin S Ho1,2

  • 1Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, 78712, TX, USA.

BMC Genomics
|July 5, 2018
PubMed
Summary

Alignment-free RNA quantification tools excel for long RNAs but struggle with small, low-abundance RNAs. This study reveals potential inaccuracies in these methods for small RNA analysis, impacting biological variation insights.

Keywords:
RNA-seqTGIRT-seqk-mer

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Area of Science:

  • Bioinformatics
  • Genomics
  • Molecular Biology

Background:

  • Alignment-free RNA quantification tools accelerate RNA sequencing (RNA-seq) analysis.
  • The accuracy of these tools for small RNAs compared to long RNAs in total RNA quantification remains unclear.

Purpose of the Study:

  • To comprehensively evaluate and compare the accuracy of four RNA-seq pipelines for gene quantification and fold-change estimation.
  • To assess the performance of alignment-free versus alignment-based pipelines specifically for small non-coding RNAs within a total RNA context.

Main Methods:

  • Utilized a novel total RNA benchmarking dataset with high representation of small non-coding RNAs and long RNAs.
  • Compared two common alignment-free pipelines against two variants of alignment-based pipelines.

Main Results:

  • All tested pipelines demonstrated high accuracy for quantifying long and highly abundant genes.
  • Alignment-free pipelines exhibited systematically poorer performance in quantifying lowly abundant and small RNAs.

Conclusions:

  • Alignment-free and alignment-based methods show similar performance for common targets like protein-coding genes.
  • Alignment-free pipelines present a potential pitfall for analyzing lowly expressed genes and small RNAs, particularly those with biological variations.