.png){kind=icon}
返回
Differences in molecular sampling and data processing explain variation among single-cell and single-nucleus RNA-seq experiments
.png){kind=icon}
OA
AI
DOI：10.1101/gr.278253.123.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A mechanistic understanding of the biological and technical factors that impact transcript measurements is essential to designing and analyzing single-cell and single-nucleus RNA sequencing experiments. Nuclei contain the same pre-mRNA population as cells, but they contain a small subset of the mRNAs. Nonetheless, early studies argued that single-nucleus analysis yielded results comparable to cellular samples if pre-mRNA measurements were included. However, typical workflows do not distinguish between pre-mRNA and mRNA when estimating gene expression, and variation in their relative abundances across cell types has received limited attention. These gaps are especially important given that incorporating pre-mRNA has become commonplace for both assays, despite known gene length bias in pre-mRNA capture. Here, we reanalyze public data sets from mouse and human to describe the mechanisms and contrasting effects of mRNA and pre-mRNA sampling on gene expression and marker gene selection in single-cell and single-nucleus RNA-seq. We show that pre-mRNA levels vary considerably among cell types, which mediates the degree of gene length bias and limits the generalizability of a recently published normalization method intended to correct for this bias. As an alternative, we repurpose an existing post hoc gene length-based correction method from conventional RNA-seq gene set enrichment analysis. Finally, we show that inclusion of pre-mRNA in bioinformatic processing can impart a larger effect than assay choice itself, which is pivotal to the effective reuse of existing data. These analyses advance our understanding of the sources of variation in single-cell and single-nucleus RNA-seq experiments and provide useful guidance for future studies.
Keyword:
ATLAS
期刊
IF:
5.5
论文数:
5.6K
被引数:
4.3W
机构
引用论文
Benchmarking single-cell RNA-sequencing protocols for cell atlas projects.png)
NATURE BIOTECHNOLOGY
OAAI
NATURE BIOTECHNOLOGYIF41.7
OAAI分享收藏The Major Risk Factors for Alzheimer's Disease: Age, Sex, and Genes Modulate the Microglia Response to Aβ PlaquesCELL REPORTSOAAI
CELL REPORTSIF6.9
OAAI分享收藏EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing dataGENOME BIOLOGYOAAI
GENOME BIOLOGYIF9.4
OAAI分享收藏分享收藏Single-Nucleus RNA-Seq Is Not Suitable for Detection of Microglial Activation Genes in Humans单核rna-seq不适合检测人类小胶质细胞激活基因CELL REPORTSOAAI
CELL REPORTSIF6.9
OAAI分享收藏
查看更多内容