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Transcriptome Analysis of Differential Allelic Representation

Bioconductor version: Release (3.19)

This package provides functions to standardise the analysis of Differential Allelic Representation (DAR). DAR compromises the integrity of Differential Expression analysis results as it can bias expression, influencing the classification of genes (or transcripts) as being differentially expressed. DAR analysis results in an easy-to-interpret value between 0 and 1 for each genetic feature 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.

Author: Lachlan Baer [aut, cre] , Stevie Pederson [aut]

Maintainer: Lachlan Baer <baerlachlan at>

Citation (from within R, enter citation("tadar")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

DAR analysis HTML R Script
Reference Manual PDF


biocViews DifferentialExpression, GenomicVariation, RNASeq, SNP, Sequencing, Software, VariantAnnotation
Version 1.2.1
In Bioconductor since BioC 3.18 (R-4.3) (0.5 years)
License GPL-3
Depends GenomicRanges, ggplot2, R (>= 4.3.0)
Imports BiocGenerics, GenomeInfoDb, Gviz, IRanges, MatrixGenerics, methods, rlang, Rsamtools, S4Vectors, stats, VariantAnnotation
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Suggests BiocStyle, covr, knitr, limma, rmarkdown, testthat (>= 3.0.0), tidyverse
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Follow Installation instructions to use this package in your R session.

Source Package tadar_1.2.1.tar.gz
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macOS Binary (x86_64) tadar_1.2.1.tgz
macOS Binary (arm64) tadar_1.2.1.tgz
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Source Repository (Developer Access) git clone
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