CircMiner: accurate and rapid detection of circular RNA through splice-aware pseudo-alignment scheme

Area of Science:

• Genomics and Bioinformatics
• Molecular Biology
• Computational Biology

Background:

• Circular RNAs (circRNAs) are abundant in eukaryotes and implicated in diseases like cancer, acting as oncogenes or tumor suppressors.
• circRNAs hold potential as disease biomarkers and therapeutic targets.
• Accurate and rapid detection of circRNAs from short sequencing reads is computationally challenging due to the complexity of identifying back-splice junctions.

Purpose of the Study:

• To introduce CircMiner, a novel, stand-alone computational method for the rapid and accurate detection of circRNAs.
• To address the computational challenges in identifying circRNAs from short sequencing reads.

Main Methods:

• CircMiner utilizes a rapid pseudo-alignment technique to efficiently identify and filter out linear RNA sequencing reads.
• The method processes remaining reads to detect back-splice junctions with single-nucleotide resolution, enabling circRNA identification.

Main Results:

• CircMiner demonstrated superior accuracy and speed compared to existing circRNA detection tools on simulated datasets.
• The tool successfully identified high-confidence circRNAs in cell line datasets, comparable to established methods.

Conclusions:

• CircMiner offers an efficient and accurate solution for circRNA detection from short sequencing reads.
• The method's performance suggests its utility in advancing circRNA research for disease biomarker and therapeutic applications.