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bioRxiv · 10.1101/2022.02.08.479579

Transformation of alignment files improves performance of variant callers for long-read RNA sequencing data

de Souza, V. B. C.·Jordan, B. T.·Tseng, E.·Nelson, E. A.·Hirschi, K. K.·Sheynkman, G. M.·Robinson, M. D.
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Abstract

Long-read RNA sequencing (lrRNA-seq) produces detailed information about full-length transcripts, including novel and sample-specific isoforms. Furthermore, there is opportunity to call variants directly from lrRNA-seq data. However, most state-of-the-art variant callers have been developed for genomic DNA. Here, there are two objectives: first, we perform a mini-benchmark on GATK, DeepVariant, Clair3, and NanoCaller primarily on PacBio Iso-Seq, data, but also on Nanopore and Illumina RNA-seq data; second, we propose a pipeline to process spliced-alignment files, making them suitable for variant calling with DNA-based callers. With such manipulations, high calling performance can be achieved using DeepVariant on Iso-seq data.

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de Souza, V. B. C., Jordan, B. T., Tseng, E., Nelson, E. A., Hirschi, K. K., Sheynkman, G. M., Robinson, M. D.. 2022-02-10. Transformation of alignment files improves performance of variant callers for long-read RNA sequencing data. https://doi.org/10.1101/2022.02.08.479579

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