GeTallele: a method for integrative analysis and visualization of DNA and RNA allele frequencies
GeTallele: a method for integrative analysis and visualization of DNA and RNA allele frequencies
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DOI：
10.1101/491209
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发表时间：
2018-12
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影响因子：
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通讯作者：
P. Słowiński;Muzi Li;P. Restrepo;Nawaf Alomran;Liam F. Spurr;Christian Miller;K. Tsaneva-Atanasova;A. Horvath
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文献类型：
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作者：
P. Słowiński;Muzi Li;P. Restrepo;Nawaf Alomran;Liam F. Spurr;Christian Miller;K. Tsaneva-Atanasova;A. Horvath
Background Asymmetric allele expression typically indicates functional and/or structural features associated with the underlying genetic variants. When integrated, RNA and DNA allele frequencies can reveal patterns characteristic of a wide-range of biological traits, including ploidy changes, genome admixture, allele-specific expression and gene-dosage transcriptional response. Results To assess RNA and DNA allele frequencies from matched sequencing datasets, we introduce a method for generating model distributions of variant allele frequencies (VAF) with a given variant read probability. In contrast to other methods, based on whole sequences or single SNV, proposed methodology uses continuous multi-SNV genomic regions. The methodology is implemented in a GeTallele toolbox that provides a suite of functions for integrative analysis, statistical assessment and visualization of Genome and Transcriptome allele frequencies. Using model VAF probabilities, GeTallele allows estimation and comparison of variant read probabilities (VAF distributions) in a sequencing dataset. We demonstrate this functionality across cancer DNA and RNA sequencing datasets. Conclusion Based on our evaluation, variant read probabilities can serve as a dependable indicator to assess gene and chromosomal allele asymmetries and to aid calls of genomic events in matched sequencing RNA and DNA datasets. Contact P.M.Slowinski@exeter.ac.uk
