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AllelicImbalance: an R/ bioconductor package for detecting,managing, and visualizing allele expression imbalance data from RNA sequencing
Authors:Jesper R G?din  Ferdinand M van’t Hooft  Per Eriksson  Lasse Folkersen
Institution:.Atherosclerosis Research Unit, Karolinska University Hospital Solna, Center for Molecular Medicine, Bldg L8:03, S-171 76 Stockholm, Sweden ;.Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, 2800 Lyngby, Denmark
Abstract:

Background

One aspect in which RNA sequencing is more valuable than microarray-based methods is the ability to examine the allelic imbalance of the expression of a gene. This process is often a complex task that entails quality control, alignment, and the counting of reads over heterozygous single-nucleotide polymorphisms. Allelic imbalance analysis is subject to technical biases, due to differences in the sequences of the measured alleles. Flexible bioinformatics tools are needed to ease the workflow while retaining as much RNA sequencing information as possible throughout the analysis to detect and address the possible biases.

Results

We present AllelicImblance, a software program that is designed to detect, manage, and visualize allelic imbalances comprehensively. The purpose of this software is to allow users to pose genetic questions in any RNA sequencing experiment quickly, enhancing the general utility of RNA sequencing. The visualization features can reveal notable, non-trivial allelic imbalance behavior over specific regions, such as exons.

Conclusions

The software provides a complete framework to perform allelic imbalance analyses of aligned RNA sequencing data, from detection to visualization, within the robust and versatile management class, ASEset.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0620-2) contains supplementary material, which is available to authorized users.
Keywords:Allelic imbalance  Allele-specific expression  RNA sequencing  Gene expression  SNP
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