Article

Cell-type classification of cancer single-cell RNA-seq data using the Subsemble ensemble-based machine learning classifier

2023-04-14

Abstract excerpt

<h4>Background: </h4> The advent of single-cell RNA sequencing (scRNA-seq) has provided a high-resolution overview of the cellular heterogeneity of different tissue types. Manual cell type annotation of gene expression datasets remains a useful but time-intensive task. Ensemble machine learning methods leverage the predictive power of multiple classifiers and can be applied to classify high-dimensional gene expres...

Topics

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

Identifiers and source

Literature Corpus work: df5633f0-730d-5e79-9754-ad8389a0f30f
DOI: 10.12688/f1000research.125579.1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Cell-type classification of cancer single-cell RNA-seq data using the Subsemble ensemble-based machine learning classifierDOI 10.12688/f1000research.125579.1Read

Imbalance and Composition Correction Ensemble Learning Framework (ICCELF): A novel framework for automated scRNA-seq cell type annotationSemantic proximity Read

Evaluation of machine learning approaches for cell-type identification from single-cell transcriptomics data.Semantic proximity Read

A Hybrid Deep Clustering Approach for Robust Cell Type Profiling Using Single-cell RNA-seq DataSemantic proximity Read

PanClassif: Improving pan cancer classification of single cell RNA-seq gene expression data using machine learningSemantic proximity Read

Estimation of immune cell content in tumor using single-cell RNA-seq reference dataSemantic proximity Read

Cell-type Annotation with Accurate Unseen Cell-type Identification Using Multiple ReferencesSemantic proximity Read

Phenotype-guided subpopulation identification from single-cell sequencing dataSemantic proximity Read

SC3 - consensus clustering of single-cell RNA-Seq dataSemantic proximity Read

Benchmarking Machine Learning Models for Cell Type Annotation in Single-Cell vs Single-Nucleus RNA-Seq DataSemantic proximity Read

Cell type composition drives patient stratification in single-cell RNA-seq cohortsSemantic proximity Read

Evaluation of methods to assign cell type labels to cell clusters from single-cell RNA-sequencing dataSemantic proximity Read

scPred: Cell type prediction at single-cell resolutionSemantic proximity Read