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  4. Avoiding false discoveries in single-cell RNA-seq by revisiting the first Alzheimer's disease dataset
 
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Avoiding false discoveries in single-cell RNA-seq by revisiting the first Alzheimer's disease dataset
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Avoiding false discoveries in single-cell RNA-seq by revisiting the first Alzheimers disease dataset.pdf (480.62 KB)
Published version
Author(s)
Murphy, Alan E
Fancy, Nurun
Skene, Nathan
Type
Journal Article
Abstract
Mathys et al. conducted the first single-nucleus RNA-seq (snRNA-seq) study of Alzheimer's disease (AD) (Mathys et al., 2019). With bulk RNA-seq, changes in gene expression across cell types can be lost, potentially masking the differentially expressed genes (DEGs) across different cell types. Through the use of single-cell techniques, the authors benefitted from increased resolution with the potential to uncover cell type-specific DEGs in AD for the first time. However, there were limitations in both their data processing and quality control and their differential expression analysis. Here, we correct these issues and use best-practice approaches to snRNA-seq differential expression, resulting in 549 times fewer DEGs at a false discovery rate of 0.05. Thus, this study highlights the impact of quality control and differential analysis methods on the discovery of disease-associated genes and aims to refocus the AD research field away from spuriously identified genes.
Date Issued
2023-12-04
Date Acceptance
2023-11-16
Citation
eLife, 2023, 12
URI
http://hdl.handle.net/10044/1/109535
URL
https://elifesciences.org/articles/90214
DOI
https://www.dx.doi.org/10.7554/eLife.90214
ISSN
2050-084X
Publisher
eLife Sciences Publications Ltd
Journal / Book Title
eLife
Volume
12
Copyright Statement
© 2023, Murphy et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
License URL
https://creativecommons.org/licenses/by/4.0/
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/38047913
Subjects
Alzheimer Disease
Humans
Quality Control
RNA, Small Nuclear
RNA-Seq
Single-Cell Gene Expression Analysis
Alzheimer's disease
chromosomes
gene expression
human
neuroscience
single-cell
single-nucleus
Publication Status
Published
Coverage Spatial
England
Article Number
90214
Date Publish Online
2023-12-04
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