dStruct: identifying differentially reactive regions from RNA structurome profiling data

RNA biology is revolutionized by recent developments of diverse high-throughput technologies for transcriptome-wide profiling of molecular RNA structures. RNA structurome profiling data can be used to identify differentially structured regions between groups of samples. Existing methods are limited in scope to specific technologies and/or do not account for biological variation. Here, we present dStruct which is the first broadly applicable method for differential analysis accounting for biological variation in structurome profiling data. dStruct is compatible with diverse profiling technologies, is validated with experimental data and simulations, and outperforms existing methods.

• Publication year

  2019

• Venue

  Genome Biology

• Publication date

  2019-02-21

• Fields of study

  Biology, Medicine, Computer Science

• Identifiers
  DOI 10.1186/s13059-019-1641-3PMID 30791935PMCID 6385470
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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