Article

New algorithms for unsupervised cell clustering from scRNA-seq data

2024-11-23

Abstract excerpt

The identification of cell types is a basic step of the pipeline for Single-Cell RNA sequencing data analysis. However, unsupervised clustering of cells from scRNA-seq data has multiple challenges: the high dimensional nature of the data, the sparse nature of the gene expression matrix, and the presence of technical noise that can introduce false zero entries. In this study, we introduce new algorithms for cluster...

Topics

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

Identifiers and source

Literature Corpus work: 1cb355cc-fa9d-5d1a-b9fb-d48c95b815b3
DOI: 10.1101/2024.11.22.624768

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

New algorithms for unsupervised cell clustering from scRNA-seq dataDOI 10.1101/2024.11.22.624768Read

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

Unsupervised multi-scale clustering of single-cell transcriptomes to identify hierarchical structures of cell subtypesSemantic proximity Read

A Fully Automated, Data-Driven Approach for Dimensionality Reduction and Clustering in Single-Cell RNA-seq AnalysisSemantic proximity Read

Unsupervised cell functional annotation for single-cell RNA-SeqSemantic proximity Read

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

Robust clustering and interpretation of scRNA-seq data using reference component analysisSemantic proximity Read

Graph Contrastive Learning as a Versatile Foundation for Advanced scRNA-seq Data AnalysisSemantic proximity Read

CellSIUS provides sensitive and specific detection of rare cell populations from complex single cell RNA-seq dataSemantic proximity Read

scAURA: Alignment- and Uniformity-based Graph Debiased Contrastive Representation Architecture for Self-Supervised Clustering of Single-Cell TranscriptomicsSemantic proximity Read

A Joint Deep Learning Model for Simultaneous Batch Effect Correction, Denoising and Clustering in Single-Cell TranscriptomicsSemantic proximity Read

scGNN: a novel graph neural network framework for single-cell RNA-Seq analysesSemantic proximity Read

Cluster decomposition-based anomaly detection for rare cell identification in single-cell expression dataSemantic proximity Read