tadar is a package designed to enable Transcriptome Analysis of Differential Allelic Representation (DAR).
DAR is parsimoniously defined as an unequal distribution of polymorphic loci between experimental sample groups; a situation likely to be encountered in RNA-seq experiments involving organisms that lack isogenicity.
When unequally-represented polymorphic loci are also expression quantitative trait loci (eQTLs), differences in gene expression between groups can be incorrectly interpreted as a consequence of the experimental condition.
DAR analysis is therefore recommended as a complementary technique alongside Differential Expression analysis.
DAR analysis results in an easy-to-interpret value between 0 and 1 for each feature (e.g. gene) of interest, where 0 represents identical allelic representation and 1 represents complete diversity.
This metric can be used to identify features prone to false-positive calls in Differential Expression analysis, and can be leveraged with statistical methods to alleviate the impact of such artefacts on RNA-seq data.
An example of the application of DAR analysis can be found in our manuscript.
Installation
BiocManager is recommended for the installation of this package.
tadar
tadaris a package designed to enable Transcriptome Analysis of Differential Allelic Representation (DAR).DAR is parsimoniously defined as an unequal distribution of polymorphic loci between experimental sample groups; a situation likely to be encountered in RNA-seq experiments involving organisms that lack isogenicity. When unequally-represented polymorphic loci are also expression quantitative trait loci (eQTLs), differences in gene expression between groups can be incorrectly interpreted as a consequence of the experimental condition. DAR analysis is therefore recommended as a complementary technique alongside Differential Expression analysis. DAR analysis results in an easy-to-interpret value between 0 and 1 for each feature (e.g. gene) of interest, where 0 represents identical allelic representation and 1 represents complete diversity. This metric can be used to identify features prone to false-positive calls in Differential Expression analysis, and can be leveraged with statistical methods to alleviate the impact of such artefacts on RNA-seq data.
An example of the application of DAR analysis can be found in our manuscript.
Installation
BiocManageris recommended for the installation of this package.The development version of this package can also be installed from GitHub.