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

Authors: Vladimir B. C. de Souza; Ben T. Jordan; Elizabeth Tseng; Elizabeth A. Nelson; Karen K. Hirschi; Gloria Sheynkman; Mark D. Robinson;

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

Abstract

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.

Country
Switzerland
Keywords

QH301-705.5, Sequence Analysis, RNA, Short Report, High-Throughput Nucleotide Sequencing, QH426-470, 10124 Institute of Molecular Life Sciences, 1307 Cell Biology, 1105 Ecology, Evolution, Behavior and Systematics, 1311 Genetics, Exome Sequencing, Genetics, 570 Life sciences; biology, RNA, RNA-Seq, Biology (General)

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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