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bioRxiv · 10.1101/2021.03.26.437240

Haplotype-aware pantranscriptome analyses using spliced pangenome graphs

Sibbesen, J. A.·Eizenga, J. M.·Novak, A. M.·Siren, J.·Chang, X.·Garrison, E.·Paten, B.
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Abstract

Pangenomics is emerging as a powerful computational paradigm in bioinformatics. This field uses population-level genome reference structures, typically consisting of a sequence graph, to mitigate reference bias and facilitate analyses that were challenging with previous reference-based methods. In this work, we extend these methods into transcriptomics to analyze sequencing data using the pantranscriptome: a population-level transcriptomic reference. Our novel toolchain can construct spliced pangenome graphs, map RNA-seq data to these graphs, and perform haplotype-aware expression quantification of transcripts in a pantranscriptome. This workflow improves accuracy over state-of-the-art RNA-seq mapping methods, and it can efficiently quantify haplotype-specific transcript expression without needing to characterize a samples haplotypes beforehand.

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Sibbesen, J. A., Eizenga, J. M., Novak, A. M., Siren, J., Chang, X., Garrison, E., Paten, B.. 2021-03-28. Haplotype-aware pantranscriptome analyses using spliced pangenome graphs. https://doi.org/10.1101/2021.03.26.437240

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