Haplotype-aware pantranscriptome analyses using spliced pangenome graphs.
Nat Methods
; 20(2): 239-247, 2023 02.
Article
em En
| MEDLINE
| ID: mdl-36646895
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 toolchain, which consists of additions to the VG toolkit and a standalone tool, RPVG, can construct spliced pangenome graphs, map RNA sequencing data to these graphs, and perform haplotype-aware expression quantification of transcripts in a pantranscriptome. We show that this workflow improves accuracy over state-of-the-art RNA sequencing mapping methods, and that it can efficiently quantify haplotype-specific transcript expression without needing to characterize the haplotypes of a sample beforehand.
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Base de dados:
MEDLINE
Assunto principal:
Biologia Computacional
/
Perfilação da Expressão Gênica
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article