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Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
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Deriving Ranges of Optimal Estimated Transcript Expression due to Nonidentifiability.

Hongyu Zheng1, Cong Ma2, Carl Kingsford1

  • 1Computational Biology Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|January 18, 2022
PubMed
Summary

RNA-seq quantification errors due to nonidentifiability affect many transcripts. New methods provide a confidence range for expression, revealing potential inaccuracies in transcript abundance estimates.

Keywords:
alternative splicingexpression quantificationnonidentifiability and differential expressionuncertainty

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Current RNA-seq expression quantification methods face a significant challenge: nonunique, equally likely estimates for transcript abundances.
  • This nonidentifiability issue is worsened by incomplete reference transcriptomes, leading to potential errors in determining true gene expression.
  • Unannotated transcripts can also contribute reads, further complicating accurate quantification.

Purpose of the Study:

  • To develop and propose methods for calculating a "confidence range of expression" for each transcript.
  • To quantify the extent of potential estimation errors caused by nonidentifiability in RNA-seq data.
  • To assess the reliability of transcript expression comparisons within samples and between groups.

Main Methods:

  • Generalized transcript quantification using graph-based approaches to account for reference incompleteness.
  • Developed methods to compute a confidence range for transcript expression, reflecting possible abundance values across optimal estimates.
  • Applied these methods to the Human Body Map dataset for analysis.

Main Results:

  • 35%-50% of transcripts show potential quantification inaccuracies due to nonidentifiability.
  • For 20%-47% of transcripts, expression ranking among isoforms within a gene is indeterminate due to quantification errors.
  • Most differentially expressed transcripts are reliable in group comparisons, though exceptions exist after considering expression ranges.

Conclusions:

  • Nonidentifiability is a pervasive issue in RNA-seq quantification, impacting a substantial portion of transcripts.
  • The proposed confidence range method effectively highlights transcripts with potential quantification errors and their severity.
  • While many differential expression findings are robust, careful consideration of expression ranges is necessary for accurate biological interpretation.