Cargando…

TransCluster: A Cell-Type Identification Method for single-cell RNA-Seq data using deep learning based on transformer

Recent advances in single-cell RNA sequencing (scRNA-seq) have accelerated the development of techniques to classify thousands of cells through transcriptome profiling. As more and more scRNA-seq data become available, supervised cell type classification methods using externally well-annotated sourc...

Descripción completa

Detalles Bibliográficos
Autores principales:	Song, Tao, Dai, Huanhuan, Wang, Shuang, Wang, Gan, Zhang, Xudong, Zhang, Ying, Jiao, Linfang
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2022
Materias:	Genetics
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9592860/ https://www.ncbi.nlm.nih.gov/pubmed/36303549 http://dx.doi.org/10.3389/fgene.2022.1038919

Ejemplares similares

scTransSort: Transformers for Intelligent Annotation of Cell Types by Gene Embeddings
por: Jiao, Linfang, et al.
Publicado: (2023)

MulCNN: An efficient and accurate deep learning method based on gene embedding for cell type identification in single-cell RNA-seq data
por: Jiao, Linfang, et al.
Publicado: (2023)

Clustering CITE-seq data with a canonical correlation-based deep learning method
por: Yuan, Musu, et al.
Publicado: (2022)

CBA: Cluster-Guided Batch Alignment for Single Cell RNA-seq
por: Yu, Wenbo, et al.
Publicado: (2021)

EC-PGMGR: Ensemble Clustering Based on Probability Graphical Model With Graph Regularization for Single-Cell RNA-seq Data
por: Zhu, Yuan, et al.
Publicado: (2020)

The Novel Key Genes of Non-obstructive Azoospermia Affect Spermatogenesis: Transcriptomic Analysis Based on RNA-Seq and scRNA-Seq Data
por: He, Haihong, et al.
Publicado: (2021)

Single-Cell RNA-Seq and Bulk RNA-Seq Reveal Intratumoral Heterogeneity and Tumor Microenvironment Characteristics in Diffuse Large B-Cell Lymphoma
por: Zhao, Yang, et al.
Publicado: (2022)

Leveraging Single-Cell RNA-seq Data to Uncover the Association Between Cell Type and Chronic Liver Diseases
por: Ye, Xiangyu, et al.
Publicado: (2021)

Integrative RNA-Seq and ATAC-Seq Analysis Reveals the Migration-Associated Genes Involved in Antitumor Effects of Herbal Medicine Feiyanning on Lung Cancer Cells
por: Wang, Chenyang, et al.
Publicado: (2021)

Multi-TransDTI: Transformer for Drug–Target Interaction Prediction Based on Simple Universal Dictionaries with Multi-View Strategy
por: Wang, Gan, et al.
Publicado: (2022)

SCSA: A Cell Type Annotation Tool for Single-Cell RNA-seq Data
por: Cao, Yinghao, et al.
Publicado: (2020)

Benchmarking automated cell type annotation tools for single-cell ATAC-seq data
por: Wang, Yuge, et al.
Publicado: (2022)

Digitaldlsorter: Deep-Learning on scRNA-Seq to Deconvolute Gene Expression Data
por: Torroja, Carlos, et al.
Publicado: (2019)

Dissecting Cellular Heterogeneity Based on Network Denoising of scRNA-seq Using Local Scaling Self-Diffusion
por: Duan, Xin, et al.
Publicado: (2022)

MicroRNAs Involved in Regulatory Cytoplasmic Male Sterility by Analysis RNA-seq and Small RNA-seq in Soybean
por: Zhang, Chunbao, et al.
Publicado: (2021)

A Comparison for Dimensionality Reduction Methods of Single-Cell RNA-seq Data
por: Xiang, Ruizhi, et al.
Publicado: (2021)

Single-Cell RNA-Seq of Bone Marrow Cells in Aplastic Anemia
por: Tonglin, Hu, et al.
Publicado: (2022)

D3K: The Dissimilarity-Density-Dynamic Radius K-means Clustering Algorithm for scRNA-Seq Data
por: Liu, Guoyun, et al.
Publicado: (2022)

ProtTrans-Glutar: Incorporating Features From Pre-trained Transformer-Based Models for Predicting Glutarylation Sites
por: Indriani, Fatma, et al.
Publicado: (2022)

Corrigendum: Digitaldlsorter: Deep-Learning on scRNA-Seq to Deconvolute Gene Expression Data
por: Torroja, Carlos, et al.
Publicado: (2020)

An Adaptive Sparse Subspace Clustering for Cell Type Identification
por: Zheng, Ruiqing, et al.
Publicado: (2020)

RFCell: A Gene Selection Approach for scRNA-seq Clustering Based on Permutation and Random Forest
por: Zhao, Yuan, et al.
Publicado: (2021)

Identification of a Five-mRNA Signature as a Novel Potential Prognostic Biomarker for Glioblastoma by Integrative Analysis
por: Xu, Huifang, et al.
Publicado: (2022)

Genome-Wide Analyses of the Genetic Screening of C(2)H(2)-Type Zinc Finger Transcription Factors and Abiotic and Biotic Stress Responses in Tomato (Solanum lycopersicum) Based on RNA-Seq Data
por: Zhao, Tingting, et al.
Publicado: (2020)

Reconstructing the Developmental Trajectories of Multiple Subtypes in Pulmonary Parenchymal Epithelial Cells by Single-Cell RNA-seq
por: Huang, Yiwei, et al.
Publicado: (2020)

Identification of COVID-19 severity biomarkers based on feature selection on single-cell RNA-Seq data of CD8(+) T cells
por: Lu, Jian, et al.
Publicado: (2022)

Identification of candidate genes controlling chilling tolerance of rice in the cold region at the booting stage by BSA-Seq and RNA-Seq
por: Guo, Zhenhua, et al.
Publicado: (2020)

Dice-XMBD: Deep Learning-Based Cell Segmentation for Imaging Mass Cytometry
por: Xiao, Xu, et al.
Publicado: (2021)

Comparative evaluation of DNase-seq footprint identification strategies
por: Barozzi, Iros, et al.
Publicado: (2014)

Enhancement and Imputation of Peak Signal Enables Accurate Cell-Type Classification in scATAC-seq
por: Cui, Zhe, et al.
Publicado: (2021)

Single-Cell RNA-Seq Technologies and Related Computational Data Analysis
por: Chen, Geng, et al.
Publicado: (2019)

Normalization Methods on Single-Cell RNA-seq Data: An Empirical Survey
por: Lytal, Nicholas, et al.
Publicado: (2020)

Non-linear Normalization for Non-UMI Single Cell RNA-Seq
por: Wu, Zhijin, et al.
Publicado: (2021)

Identification of shared biological features in four different lung cell lines infected with SARS-CoV-2 virus through RNA-seq analysis
por: Zhang, Xiaoxi, et al.
Publicado: (2023)

AdImpute: An Imputation Method for Single-Cell RNA-Seq Data Based on Semi-Supervised Autoencoders
por: Xu, Li, et al.
Publicado: (2021)

Identification of potential models for predicting progestin insensitivity in patients with endometrial atypical hyperplasia and endometrioid endometrial cancer based on ATAC-Seq and RNA-Seq integrated analysis
por: Hu, Jia-Li, et al.
Publicado: (2022)

DeepLION: Deep Multi-Instance Learning Improves the Prediction of Cancer-Associated T Cell Receptors for Accurate Cancer Detection
por: Xu, Ying, et al.
Publicado: (2022)

Corrigendum: Comparative evaluation of DNase-seq footprint identification strategies
por: Barozzi, Iros, et al.
Publicado: (2014)

Identifying differential transcription factor binding in ChIP-seq
por: Wu, Dai-Ying, et al.
Publicado: (2015)

RNA-seq of Ranunculus sceleratus and Identification of Orthologous Genes among Four Ranunculus Species
por: Zhao, Shu-Ying, et al.
Publicado: (2016)

Cannot write session to /tmp/vufind_sessions/sess_31jtnol19ekr6chue8qjksngmr