Bioinformatics & Computational Biology
Program in Bioinformatics and Integrative Biology
Bioinformatics | Computational Biology
We introduce RNA2DNAlign, a computational framework for quantitative assessment of allele counts across paired RNA and DNA sequencing datasets. RNA2DNAlign is based on quantitation of the relative abundance of variant and reference read counts, followed by binomial tests for genotype and allelic status at SNV positions between compatible sequences. RNA2DNAlign detects positions with differential allele distribution, suggesting asymmetries due to regulatory/structural events. Based on the type of asymmetry, RNA2DNAlign outlines positions likely to be implicated in RNA editing, allele-specific expression or loss, somatic mutagenesis or loss-of-heterozygosity (the first three also in a tumor-specific setting). We applied RNA2DNAlign on 360 matching normal and tumor exomes and transcriptomes from 90 breast cancer patients from TCGA. Under high-confidence settings, RNA2DNAlign identified 2038 distinct SNV sites associated with one of the aforementioned asymetries, the majority of which have not been linked to functionality before. The performance assessment shows very high specificity and sensitivity, due to the corroboration of signals across multiple matching datasets. RNA2DNAlign is freely available from http://github.com/HorvathLab/NGS as a self-contained binary package for 64-bit Linux systems.
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© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. Citation: Nucleic Acids Res. 2016 Dec 15;44(22):e161. Epub 2016 Aug 30. Link to article on publisher's website
Nucleic acids research
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This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Movassagh, Mercedeh; Alomran, Nawaf; Mudvari, Prakriti; Dede, Merve; Dede, Cem; Kowsari, Kamran; Restrepo, Paula; Cauley, Edmund; Bahl, Sonali; Li, Muzi; Waterhouse, Wesley; Tsaneva-Atanasova, Krasimira; Edwards, Nathan; and Horvath, Anelia, "RNA2DNAlign: nucleotide resolution allele asymmetries through quantitative assessment of RNA and DNA paired sequencing data." (2016). GSBS Student Publications. 1998.