cisASE: a likelihood-based method for detecting putative cis-regulated allele-specific expression in RNA sequencing...

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Allele-specific expression (ASE) is crucial for identifying cis-acting regulatory variations.
• These variations offer potential for developing novel therapeutic strategies by modulating specific alleles.
• Current methods for identifying ASE in next-generation sequencing (NGS) data face several limitations.

Purpose of the Study:

• To develop a robust and efficient method for detecting allele-specific expression (ASE).
• To identify cis-acting regulatory variations at single nucleotide variant (SNV), exon, and gene levels.
• To provide a tool applicable to various sequencing datasets, including those without parental information or phasing.

Main Methods:

• Developed cisASE, a likelihood-based method for ASE detection.
• Utilized matched DNA-seq data to control for technical bias and copy number variation (CNV).
• Evaluated cisASE performance against state-of-the-art methods in terms of accuracy and speed.

Main Results:

• cisASE demonstrated significantly increased accuracy and speed compared to existing methods.
• The method effectively identifies ASE at SNV, exon, and gene levels without phasing or parental data.
• cisASE showed moderate performance even without DNA-seq data, enhancing its applicability.
• Analysis of real datasets revealed distinct ASE characteristics in normal and cancer tissues.

Conclusions:

• cisASE is an accurate and fast tool for detecting allele-specific expression.
• The method is widely applicable and robust, even with limited data.
• cisASE has significant potential for applications in cancer genomics and personalized medicine.