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Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
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SeqOthello: querying RNA-seq experiments at scale.

Ye Yu1, Jinpeng Liu1, Xinan Liu1

  • 1Department of Computer Science, University of Kentucky, 301 Rose St, Lexington, KY, 40508, USA.

Genome Biology
|October 21, 2018
PubMed
Summary
This summary is machine-generated.

SeqOthello is a fast, memory-efficient tool for querying large RNA sequencing (RNA-seq) datasets. It identifies fusion events, including novel tumor-specific ones, enabling large-scale genomic studies.

Keywords:
CompressionGene fusionOthelloPan-cancerQueryRNA-seqSeqOthelloTCGA

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • Large-scale RNA sequencing (RNA-seq) data analysis presents computational challenges.
  • Efficient querying of fusion events across numerous datasets is crucial for cancer research.

Purpose of the Study:

  • To introduce SeqOthello, an indexing structure for rapid and memory-efficient sequence querying.
  • To enable comprehensive analysis of RNA-seq data for identifying fusion events.

Main Methods:

  • Development of SeqOthello, an ultra-fast and memory-efficient indexing structure.
  • Application of SeqOthello to query 10,113 TCGA Pan-Cancer RNA-seq datasets for fusion events.

Main Results:

  • SeqOthello processed 11,658 fusion events in 5 minutes using 19.1 GB memory.
  • Identified 92.7% of tier-1 fusions and 270 novel, tumor-specific fusion events.
  • Demonstrated reference-free, alignment-free, and parameter-free sequence search capabilities.

Conclusions:

  • SeqOthello significantly enhances the feasibility of large-scale integrative studies using sequence-level data.
  • The tool facilitates the discovery of novel tumor-specific fusion events.
  • Enables individual labs to conduct previously impracticable large-scale genomic analyses.