scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1471-2105

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data ; volume:22 ; number:1 ; day:12 ; month:4 ; year:2021 ; pages:1-15 ; date:12.2021
BMC bioinformatics ; 22, Heft 1 (12.4.2021), 1-15, 12.2021

Creator: Ranjan, Bobby
Schmidt, Florian
Sun, Wenjie
Park, Jinyu
Honardoost, Mohammad Amin
Tan, Joanna
Arul Rayan, Nirmala
Prabhakar, Shyam

Contributor: SpringerLink (Online service)

DOI: 10.1186/s12859-021-04028-4

URN: urn:nbn:de:101:1-2021060122200622903059

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:50 AM CEST

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Ranjan, Bobby
Schmidt, Florian
Sun, Wenjie
Park, Jinyu
Honardoost, Mohammad Amin
Tan, Joanna
Arul Rayan, Nirmala
Prabhakar, Shyam
SpringerLink (Online service)

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scSemiAAE: a semi-supervised clustering model for single-cell RNA-seq data

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Bayesian Inference for Single-cell Clustering and Imputing

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scConsensus: combining supervised and unsupervised clustering for cell type identification in single-cell RNA sequencing data

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Other Objects (12)

scSemiAAE: a semi-supervised clustering model for single-cell RNA-seq data

Unsupervised clustering and epigenetic classification of single cells

Semi-supervised integration of single-cell transcriptomics data

Adapted single-cell consensus clustering (adaSC3)

Assessing consistency of (single-cell) unsupervised multi-modal methods

JOINTLY: interpretable joint clustering of single-cell transcriptomes

scSTEM: clustering pseudotime ordered single-cell data

Bayesian Inference for Single-cell Clustering and Imputing

Unsupervised and supervised discovery of tissue cellular neighborhoods from cell phenotypes

Supervised discovery of interpretable gene programs from single-cell data

Supervised median clustering

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scSemiAAE: a semi-supervised clustering model for single-cell RNA-seq data

Unsupervised clustering and epigenetic classification of single cells

Semi-supervised integration of single-cell transcriptomics data

Adapted single-cell consensus clustering (adaSC3)

Assessing consistency of (single-cell) unsupervised multi-modal methods

JOINTLY: interpretable joint clustering of single-cell transcriptomes

scSTEM: clustering pseudotime ordered single-cell data

Bayesian Inference for Single-cell Clustering and Imputing

Unsupervised and supervised discovery of tissue cellular neighborhoods from cell phenotypes

Supervised discovery of interpretable gene programs from single-cell data

Supervised median clustering

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scSemiAAE: a semi-supervised clustering model for single-cell RNA-seq data

Unsupervised clustering and epigenetic classification of single cells

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JOINTLY: interpretable joint clustering of single-cell transcriptomes

scSTEM: clustering pseudotime ordered single-cell data

Bayesian Inference for Single-cell Clustering and Imputing

Unsupervised and supervised discovery of tissue cellular neighborhoods from cell phenotypes

Supervised discovery of interpretable gene programs from single-cell data

Supervised median clustering

Mining of Cell Assay Images Using Active Semi-Supervised-Clustering

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