Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

A comparison of marker gene selection methods for single-cell RNA sequencing data

26 Feb 2024

Abstract excerpt

BACKGROUND: The development of single-cell RNA sequencing (scRNA-seq) has enabled scientists to catalog and probe the transcriptional heterogeneity of individual cells in unprecedented detail. A common step in the analysis of scRNA-seq data is the selection of so-called marker genes, most commonly to enable annotation of the biological cell types present in the sample. In this paper, we benchmark 59 computational...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Ferroptosis and cancer prognosis
Share to Gene expression and cancer classification
Share to Single-cell and spatial transcriptomics

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 38409056
DOI: 10.1186/s13059-024-03183-0

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

A comparison of marker gene selection methods for single-cell RNA sequencing dataPMID 38409056Read ↗

Fully-automated and ultra-fast cell-type identification using specific marker combinations from single-cell transcriptomic dataSemantic proximity Read ↗

Discovery of optimal cell type classification marker genes from single cell RNA sequencing dataSemantic proximity Read ↗

Discovery of optimal cell type classification marker genes from single cell RNA sequencing dataSemantic proximity Read ↗

Feature extraction approach in single-cell gene expression profiling for cell-type marker identificationSemantic proximity Read ↗

singleCellBase: a high-quality manually curated database of cell markers for single cell annotation across multiple speciesSemantic proximity Read ↗

CFMF: A Clustering-Free Cell Marker Finder for Single-Cell Transcriptomics DataSemantic proximity Read ↗

Stabilized marker gene identification and functional annotation from single-cell transcriptomic dataSemantic proximity Read ↗

<i>easybio</i> : an R Package for Single-Cell Annotation with CellMarker2.0Semantic proximity Read ↗

scQuery: a web server for comparative analysis of single-cell RNA-seq dataSemantic proximity Read ↗

Discovering cell types underlying rare disease phenotypes using scRNA-seq data from non-diseased tissuesSemantic proximity Read ↗

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

Sincast: a computational framework to predict cell identities in single-cell transcriptomes using bulk atlases as references.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.