VASC: dimension reduction and visualization of single-cell RNA-seq data by deep variational autoencoder
Single-cell RNA sequencing (scRNA-seq) is a powerful technique to analyze the
transcriptomic heterogeneities at the single cell level. It is an important step for studying cell …
transcriptomic heterogeneities at the single cell level. It is an important step for studying cell …
Dimensionality reduction and visualization of single-cell RNA-seq data with an improved deep variational autoencoder
Single-cell RNA sequencing (scRNA-seq) is a revolutionary breakthrough that determines
the precise gene expressions on individual cells and deciphers cell heterogeneity and …
the precise gene expressions on individual cells and deciphers cell heterogeneity and …
A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis
Background Single-cell RNA sequencing (scRNA-seq) is an emerging technology that can
assess the function of an individual cell and cell-to-cell variability at the single cell level in an …
assess the function of an individual cell and cell-to-cell variability at the single cell level in an …
A topology-preserving dimensionality reduction method for single-cell RNA-seq data using graph autoencoder
Dimensionality reduction is crucial for the visualization and interpretation of the high-
dimensional single-cell RNA sequencing (scRNA-seq) data. However, preserving …
dimensional single-cell RNA sequencing (scRNA-seq) data. However, preserving …
Combining gene ontology with deep neural networks to enhance the clustering of single cell RNA-Seq data
J Peng, X Wang, X Shang - BMC bioinformatics, 2019 - Springer
Background Single cell RNA sequencing (scRNA-seq) is applied to assay the individual
transcriptomes of large numbers of cells. The gene expression at single-cell level provides …
transcriptomes of large numbers of cells. The gene expression at single-cell level provides …
Parameter tuning is a key part of dimensionality reduction via deep variational autoencoders for single cell RNA transcriptomics
Single-cell RNA sequencing (scRNA-seq) is a powerful tool to profile the transcriptomes of a
large number of individual cells at a high resolution. These data usually contain …
large number of individual cells at a high resolution. These data usually contain …
Visualization of single cell RNA-seq data using t-SNE in R
Single cell RNA sequencing (scRNA-seq) is a powerful tool to analyze cellular
heterogeneity, identify new cell types, and infer developmental trajectories, which has …
heterogeneity, identify new cell types, and infer developmental trajectories, which has …
A comparison for dimensionality reduction methods of single-cell RNA-seq data
R Xiang, W Wang, L Yang, S Wang, C Xu… - Frontiers in genetics, 2021 - frontiersin.org
Single-cell RNA sequencing (scRNA-seq) is a high-throughput sequencing technology
performed at the level of an individual cell, which can have a potential to understand cellular …
performed at the level of an individual cell, which can have a potential to understand cellular …
Structure-preserving visualisation of high dimensional single-cell datasets
Single-cell technologies offer an unprecedented opportunity to effectively characterize
cellular heterogeneity in health and disease. Nevertheless, visualisation and interpretation …
cellular heterogeneity in health and disease. Nevertheless, visualisation and interpretation …
Interpretable dimensionality reduction of single cell transcriptome data with deep generative models
Single-cell RNA-sequencing has great potential to discover cell types, identify cell states,
trace development lineages, and reconstruct the spatial organization of cells. However …
trace development lineages, and reconstruct the spatial organization of cells. However …