A compendium of methods: Searching allele specific expression via RNA sequencing

Diploid mammalian genome has paired alleles for each gene; typically allowing for equal expression of the two alleles within the cell/tissue. However, genetic regulatory elements and epigenetic modifications can disrupt this equality, leading to preferential expression of one allele. Examining high-confidence allele-specific expression (ASE) is vital for understanding genetic variations and their impact on major diseases like cancers and diabetes. ASE analysis not only aids in disease prognosis and diagnosis but also helps to identify regulatory mechanisms operating within the genome. While advances in sequencing technologies have greatly improved our understanding of ASE, challenges remain in estimating it accurately. In this article, we reviewed methods for detecting ASE using both bulk RNASeq and single-cell RNASeq data to provide deeper insights beyond the mere prediction of ASE genes. Fundamentally, ASE detection methods are data-driven and can be classified according to type of data used. Some methods utilize both, DNA genotyping information and RNASeq while others rely solely on RNASeq data. This article offers a comparative analysis of these methods and compilation of repositories providing valuable insights.