Abstract

MOTIVATION: The biological relevance of chimeric RNA alignments is now well established. Chimera arising as chromosomal fusions are often drivers of cancer, and recently discovered circular RNA are only now being characterized. While software already exists for fusion discovery and quantitation, high false positive rates and high run-times hamper scalable fusion discovery on large datasets. Furthermore, software available for circular RNA detection and quantification is limited.

RESULTS: Here we present STAR Chimeric Post (STARChip), a novel software package that processes chimeric alignments from the STAR aligner and produces annotated circular RNA and high precision fusions in a rapid, efficient, and scalable manner that is appropriate for high dimensional medical omics datasets.

AVAILABILITY AND IMPLEMENTATION: STARChip is available at https://github.com/LosicLab/STARChip.

CONTACTS: bojan.losic@mssm.edu or nicholas.kipp.akers@gmail.com.

SUPPLEMENTARY INFORMATION: Supplementary figures and tables are available online.