dStruct: identifying differentially reactive regions from RNA structurome profiling data

Genome Biology
Krishna ChoudharySharon Aviran

Abstract

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.

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Methods Mentioned

BETA
RNA-seq
ChIP-seq
Structure-Seq
deltaSHAPE
SHAPE-Seq
CLIP-seq
PCR
SHAPE-MaP

Software Mentioned

deltaSHAPE
Structure
ViennaRNA package
RNAsubopt (
patteRNA
RNAsubopt
ViennaRNA
cutadapt
RASA
ggplot2

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