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利用 DecontPro 对基于液滴的单细胞蛋白质表达数据中的背景噪声进行特征描述和清除。

Characterization and decontamination of background noise in droplet-based single-cell protein expression data with DecontPro.

机构信息

Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA.

Department of Mathematics and Statistics, Boston University, Boston, MA 02115, USA.

出版信息

Nucleic Acids Res. 2024 Jan 11;52(1):e4. doi: 10.1093/nar/gkad1032.

DOI:10.1093/nar/gkad1032
PMID:37973397
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10783508/
Abstract

Assays such as CITE-seq can measure the abundance of cell surface proteins on individual cells using antibody derived tags (ADTs). However, many ADTs have high levels of background noise that can obfuscate down-stream analyses. In an exploratory analysis of PBMC datasets, we find that some droplets that were originally called 'empty' due to low levels of RNA contained high levels of ADTs and likely corresponded to neutrophils. We identified a novel type of artifact in the empty droplets called a 'spongelet' which has medium levels of ADT expression and is distinct from ambient noise. ADT expression levels in the spongelets correlate to ADT expression levels in the background peak of true cells in several datasets suggesting that they can contribute to background noise along with ambient ADTs. We then developed DecontPro, a novel Bayesian hierarchical model that can decontaminate ADT data by estimating and removing contamination from these sources. DecontPro outperforms other decontamination tools in removing aberrantly expressed ADTs while retaining native ADTs and in improving clustering specificity. Overall, these results suggest that identification of empty drops should be performed separately for RNA and ADT data and that DecontPro can be incorporated into CITE-seq workflows to improve the quality of downstream analyses.

摘要

测定法,如 CITE-seq 可以使用源自抗体的标签 (ADT) 来测量单个细胞表面蛋白的丰度。然而,许多 ADT 具有高水平的背景噪声,这可能会混淆下游分析。在对 PBMC 数据集的探索性分析中,我们发现一些由于 RNA 水平低而最初被称为“空”的液滴实际上含有高水平的 ADT,可能对应于中性粒细胞。我们在空液滴中发现了一种称为“海绵体”的新型伪影,其 ADT 表达水平中等,与背景噪声明显不同。在几个数据集的真实细胞背景峰中,海绵体中的 ADT 表达水平与 ADT 表达水平相关,这表明它们可能与环境 ADT 一起导致背景噪声。然后,我们开发了 DecontPro,这是一种新颖的贝叶斯层次模型,可以通过估计和去除这些来源的污染来净化 ADT 数据。DecontPro 在去除异常表达的 ADT 而保留天然 ADT 并提高聚类特异性方面优于其他净化工具。总的来说,这些结果表明,对于 RNA 和 ADT 数据,应该分别对空液滴进行鉴定,并且可以将 DecontPro 纳入 CITE-seq 工作流程,以提高下游分析的质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c4a/10783508/152961d4ae6b/gkad1032fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c4a/10783508/201957bea71e/gkad1032figgra1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c4a/10783508/0c36032a8c98/gkad1032fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c4a/10783508/a48aa8ca3462/gkad1032fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c4a/10783508/b2a8f8238998/gkad1032fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c4a/10783508/00b9ef8af45c/gkad1032fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c4a/10783508/152961d4ae6b/gkad1032fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c4a/10783508/201957bea71e/gkad1032figgra1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c4a/10783508/0c36032a8c98/gkad1032fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c4a/10783508/a48aa8ca3462/gkad1032fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c4a/10783508/b2a8f8238998/gkad1032fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c4a/10783508/00b9ef8af45c/gkad1032fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c4a/10783508/152961d4ae6b/gkad1032fig5.jpg

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