Article

Identifying strengths and weaknesses of methods for computational network inference from single cell RNA-seq data

2021-06-02

Abstract excerpt

Single-cell RNA-sequencing (scRNA-seq) offers unparalleled insight into the transcriptional programs of different cellular states by measuring the transcriptome of thousands of individual cells. An emerging problem in the analysis of scRNA-seq is the inference of transcriptional gene regulatory networks and a number of methods with different learning frameworks have been developed to address this problem. Here, we...

Topics

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

Identifiers and source

Literature Corpus work: 5b212fd8-c670-51b7-bdab-aec33be9e211
DOI: 10.1101/2021.06.01.446671

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Identifying strengths and weaknesses of methods for computational network inference from single cell RNA-seq dataDOI 10.1101/2021.06.01.446671Read

Leveraging high-powered RNA-Seq datasets to improve inference of regulatory activity in single-cell RNA-Seq dataSemantic proximity Read

Evaluating the reproducibility of single-cell gene regulatory network inference algorithmsSemantic proximity Read

Population-level comparisons of gene regulatory networks modeled on high-throughput single-cell transcriptomics dataSemantic proximity Read

SCING: Single Cell INtegrative Gene regulatory network inference elucidates robust, interpretable gene regulatory networksSemantic proximity Read

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

SCENIC: Single-cell regulatory network inference and clusteringSemantic proximity Read

Gene regulatory network reconstruction using single-cell RNA sequencing of barcoded genotypes in diverse environments.Semantic proximity Read

Single-Cell Transcriptomics Unveils Gene Regulatory Network PlasticitySemantic proximity Read

CINS: Cell Interaction Network inference from Single cell expression dataSemantic proximity Read

Single-cell and spatial multiomic inference of gene regulatory networks using SCRIProSemantic proximity Read

Understanding transcriptional regulation through computational analysis of single-cell transcriptomicsSemantic proximity Read

AENetMoX: Fast and Precise scRNA-seq Gene Regulatory Network Inference Through Multi-Modal Feature Integration in Brain OrganoidsSemantic proximity Read