INSIDER: Interpretable sparse matrix decomposition for RNA expression data analysis

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	INSIDER: Interpretable sparse matrix decomposition for RNA expression data analysis
	Zhao, K; Huang, S; Lin, CC; Sham, PC; So, HC; Lin, ZX
	2024
发表期刊	PLOS GENETICS
ISSN	1553-7404
卷号	20 期号:3
摘要	RNA sequencing (RNA-Seq) is widely used to capture transcriptome dynamics across tissues, biological entities, and conditions. Currently, few or no methods can handle multiple biological variables (e.g., tissues/ phenotypes) and their interactions simultaneously, while also achieving dimension reduction (DR). We propose INSIDER, a general and flexible statistical framework based on matrix factorization, which is freely available at https://github.com/kai0511/insider. INSIDER decomposes variation from different biological variables and their interactions into a shared low-rank latent space. Particularly, it introduces the elastic net penalty to induce sparsity while considering the grouping effects of genes. It can achieve DR of high-dimensional data (of > = 3 dimensions), as opposed to conventional methods (e.g., PCA/NMF) which generally only handle 2D data (e.g., sample x expression). Besides, it enables computing 'adjusted' expression profiles for specific biological variables while controlling variation from other variables. INSIDER is computationally efficient and accommodates missing data. INSIDER also performed similarly or outperformed a close competing method, SDA, as shown in simulations and can handle complex missing data in RNA-Seq data. Moreover, unlike SDA, it can be used when the data cannot be structured into a tensor. Lastly, we demonstrate its usefulness via real data analysis, including clustering donors for disease subtyping, revealing neuro-development trajectory using the BrainSpan data, and uncovering biological processes contributing to variables of interest (e.g., disease status and tissue) and their interactions.
收录类别	sci
语种	英语
文献类型	期刊论文
条目标识符	http://ir.kiz.ac.cn/handle/152453/14435
专题	昆明动物研究所
推荐引用方式 GB/T 7714	Zhao, K,Huang, S,Lin, CC,et al. INSIDER: Interpretable sparse matrix decomposition for RNA expression data analysis[J]. PLOS GENETICS,2024,20(3).
APA	Zhao, K,Huang, S,Lin, CC,Sham, PC,So, HC,&Lin, ZX.(2024).INSIDER: Interpretable sparse matrix decomposition for RNA expression data analysis.PLOS GENETICS,20(3).
MLA	Zhao, K,et al."INSIDER: Interpretable sparse matrix decomposition for RNA expression data analysis".PLOS GENETICS 20.3(2024).

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2024073147.pdf（2103KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	请求全文