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Related Experiment Video

Updated: Dec 15, 2025

Analysis of Termination of Transcription Using BrUTP-strand-specific Transcription Run-on TRO Approach
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Terminus enables the discovery of data-driven, robust transcript groups from RNA-seq data.

Hirak Sarkar1,2, Avi Srivastava3, Héctor Corrada Bravo1,2

  • 1Department of Computer Science, University of Maryland, College Park, MD 20742, USA.

Bioinformatics (Oxford, England)
|July 14, 2020
PubMed
Summary
This summary is machine-generated.

RNA-seq analysis faces challenges with transcript-level abundance estimation due to inferential uncertainty. Our new method, Terminus, groups transcripts by uncertainty, enabling robust analysis at the transcript or group level.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • RNA-sequencing (RNA-seq) enables transcript-level analysis, but inferential uncertainty in abundance estimation poses challenges.
  • Gene-level analysis offers robustness but sacrifices transcript-specific resolution, even when transcript-level effects are evident.

Purpose of the Study:

  • To develop a data-driven approach for grouping transcripts based on shared inferential uncertainty.
  • To enable more robust and confident downstream analysis of RNA-seq data by managing uncertainty.

Main Methods:

  • Introduced a novel method implemented in the Terminus tool.
  • Grouped transcripts exhibiting complex patterns of ambiguously-mapping fragments.
  • Leveraged shared inferential uncertainty to reduce noise within transcript groups.

Main Results:

  • Terminus effectively groups transcripts with high shared inferential uncertainty.
  • This grouping allows for confident transcript-level analysis where possible and robust group-level analysis otherwise.
  • The approach enhances the reliability of RNA-seq data interpretation.

Conclusions:

  • Terminus provides a flexible framework for transcript-level RNA-seq analysis.
  • It balances the need for resolution with the reality of inferential uncertainty.
  • The tool facilitates more accurate biological insights from RNA-seq experiments.