Qualitative Comparison Of Selected Indel Detection Methods For Rna-Seq Data

RNA sequencing (RNA-Seq) provides both gene expression and sequence information, which can be exploited for a joint approach to explore cell processes in general and diseases caused by genomic variants in particular. However, the identification of insertions and deletions (indels) from RNA-Seq data, which for instance play a significant role in the development, detection, and treatment of cancer, still poses a challenge. In this paper, we present a qualitative comparison of selected methods for indel detection from RNA-Seq data. More specifically, we benchmarked two promising aligners and two filter methods on simulated as well as on real RNA-Seq data. We conclude that in cases where reliable detection of indels is crucial, e.g. in a clinical setting, the usage of our pipeline setup is superior to other state-of-the-art approaches.