The long and the short of it: unlocking nanopore long-read RNA sequencing data with short-read differential expression analysis tools
Publication Year 2021-06, Volume 3, Issue #2, Page lqab028
Journal Title
NAR Genomics and Bioinformatics
Application of Oxford Nanopore Technologies' long-read sequencing platform to transcriptomic analysis is increasing in popularity. However, such analysis can be challenging due to the high sequence error and small library sizes, which decreases quantification accuracy and reduces power for statistical testing. Here, we report the analysis of two nanopore RNA-seq datasets with the goal of obtaining gene- and isoform-level differential expression information. A dataset of synthetic, spliced, spike-in RNAs ('sequins') as well as a mouse neural stem cell dataset from samples with a null mutation of the epigenetic regulator Smchd1 was analysed using a mix of long-read specific tools for preprocessing together with established short-read RNA-seq methods for downstream analysis. We used limma-voom to perform differential gene expression analysis, and the novel FLAMES pipeline to perform isoform identification and quantification, followed by DRIMSeq and limma-diffSplice (with stageR) to perform differential transcript usage analysis. We compared results from the sequins dataset to the ground truth, and results of the mouse dataset to a previous short-read study on equivalent samples. Overall, our work shows that transcriptomic analysis of long-read nanopore data using long-read specific preprocessing methods together with short-read differential expression methods and software that are already in wide use can yield meaningful results.
Oxford Academic
WEHI Research Division(s)
Epigenetics And Development
PubMed ID
Open Access at Publisher's Site
NHMRC Grants
NHMRC/1098290 NHMRC/1104924 NHMRC/1072662
Rights Notice
Refer to copyright notice on published article.

Creation Date: 2021-05-11 04:12:08
Last Modified: 2021-05-17 10:05:16
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