计算机科学
规范化(社会学)
源代码
表观遗传学
计算生物学
聚类分析
预处理器
推论
瓶颈
非负矩阵分解
协议(科学)
数据挖掘
人工智能
生物
矩阵分解
DNA甲基化
社会学
替代医学
特征向量
基因表达
嵌入式系统
量子力学
病理
人类学
物理
操作系统
基因
生物化学
医学
作者
Jialin Liu,Chao Gao,Joshua Sodicoff,Velina Kozareva,Evan Z. Macosko,Joshua D. Welch
出处
期刊:Nature Protocols
[Springer Nature]
日期:2020-10-12
卷期号:15 (11): 3632-3662
被引量:96
标识
DOI:10.1038/s41596-020-0391-8
摘要
High-throughput single-cell sequencing technologies hold tremendous potential for defining cell types in an unbiased fashion using gene expression and epigenomic state. A key challenge in realizing this potential is integrating single-cell datasets from multiple protocols, biological contexts, and data modalities into a joint definition of cellular identity. We previously developed an approach, called linked inference of genomic experimental relationships (LIGER), that uses integrative nonnegative matrix factorization to address this challenge. Here, we provide a step-by-step protocol for using LIGER to jointly define cell types from multiple single-cell datasets. The main stages of the protocol are data preprocessing and normalization, joint factorization, quantile normalization and joint clustering, and visualization. We describe how to jointly define cell types from single-cell RNA-seq (scRNA-seq) and single-nucleus ATAC-seq (snATAC-seq) data, but similar steps apply across a wide range of other settings and data types, including cross-species analysis, single-nucleus DNA methylation, and spatial transcriptomics. Our protocol contains examples of expected results, describes common pitfalls, and relies only on our freely available, open-source R implementation of LIGER. We also provide R Markdown tutorials showing the outputs from each individual code segment. The analysis process can be performed in 1–4 h, depending on dataset size, and assumes no specialized bioinformatics training. Here, the authors describe step-by-step procedures for integrating single-cell sequencing datasets from different experiments or modalities to identify common and distinct cell types using the R-based software tool LIGER.
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