Article

A Markov Random Field Model for Network-based Differential Expression Analysis of Single-cell RNA-seq Data

2020-11-12

Abstract excerpt

<h4>Background</h4> Recent development of single cell sequencing technologies has made it possible to identify genes with different expression (DE) levels at the cell type level between different groups of samples. In this article, we propose to borrow information through known biological networks to increase statistical power to identify differentially expressed genes (DEGs). <h4>Results</h4> We develop MRFscRN...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 567518f3-2b24-5923-8411-924e3dca6d66
DOI: 10.1101/2020.11.11.378976

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A Markov Random Field Model for Network-based Differential Expression Analysis of Single-cell RNA-seq DataDOI 10.1101/2020.11.11.378976Read

A Markov Random Field Model for Network-based Differential Expression Analysis of Single-cell RNA-seq DataSemantic proximity Read

Bayesian-frequentist hybrid inference framework for single cell RNA-seq analysesSemantic proximity Read

Detecting cell type from single cell RNA sequencing based on deep bi-stochastic graph regularized matrix factorizationSemantic proximity Read

A Markov random field model for network-based analysis of genomic data.Semantic proximity Read

A Regularized Bayesian Dirichlet-multinomial Regression Model for Integrating Single-cell-level Omics and Patient-level Clinical Study DataSemantic proximity Read

Latent variable modelling and variational inference for scRNA-seq differential expression analysisSemantic proximity Read

Joint Gene Network Construction by Single-Cell RNA Sequencing DataSemantic proximity Read

Big data and single cell transcriptomics: implications for ontological representationSemantic proximity Read

Causal assessment of gene regulatory network in single-cell transcriptomics data based on Bayesian networksSemantic proximity Read

Scalable probabilistic matrix factorization for single-cell RNA-seq analysisSemantic proximity Read

Distribution-free complex hypothesis testing for single-cell RNA-seq differential expression analysisSemantic proximity Read

Comparative Single-Cell Transcriptomics Uncovers Shared and Distinct Molecular Signatures in Cystic Fibrosis and Primary Ciliary DyskinesiaSemantic proximity Read