id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
10_1101-727867	Tangherloni, Andrea	scAEspy: a tool for autoencoder-based analysis of single-cell RNA sequencing data	2021	28	.pdf	application/pdf	15281	2865	72	scAEspy: a tool for autoencoder-based analysis of single-cell RNA sequencing data This computational tool allows for coupling low-dimensional probabilistic representation of gene expression data with the downstream analysis to consider the Finally, the currently available AEs cannot be directly exploited to obtain the latent space or to generate synthetic cells. to show the cells in this embedded space or as a starting point for other dimensionality reduction approaches (e.g., t-SNE and UMAP) as well as downstream analyses Non-linear approaches for dimensionality reduction can be effectively used to capture the non-linearities among the gene interactions that may exist in the highdimensional expression space of scRNA-Seq data [16]. be effectively applied to analyse disparate types of single-cell data from different flexible method developed to cluster single-cell data; (ii) a centroid is calculated batch-effect correction methods for single-cell rna sequencing data. Wang, D., Gu, J.: VASC: dimension reduction and visualization of single-cell RNA-seq data by deep	./cache/10_1101-727867.pdf	./txt/10_1101-727867.txt