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Dimensionality reduction

G T A T C G C T A
Seurat
Desktop

Seurat

An R package designed for the analysis and visualization of single cell RNA-seq…

An R package designed for the analysis and visualization of single cell RNA-seq data. Seurat contains easy-to-use implementations of commonly used analytical techniques, including the identification…

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ZIFA
Desktop

ZIFA Zero Inflated Factor Analysis

Single cell RNA-seq data allows insight into normal cellular function and…

Single cell RNA-seq data allows insight into normal cellular function and diseases including cancer through the molecular characterisation of cellular state at the single-cell level. Dimensionality…

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VASC
Desktop

VASC deep Variational Autoencoder for scRNA-seq data

Analyzes and visualizes single cell RNA sequencing (scRNA-seq data). VASC is a…

Analyzes and visualizes single cell RNA sequencing (scRNA-seq data). VASC is a deep variational autoencoder can capture non-linear variations and automatically learn a hierarchical representation of…

G T A T C G C T A
scvis
Desktop

scvis

Allows users to capture and visualize the low-dimensional structures in…

Allows users to capture and visualize the low-dimensional structures in single-cell gene expression data. scvis is a robust latent variable model that allows to spot underlying low-dimensional…

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ZINB-WaVE
Desktop

ZINB-WaVE

Leads to low-dimensional representations of the data that account for zero…

Leads to low-dimensional representations of the data that account for zero inflation (dropouts), over-dispersion, and the count nature of the data. ZINB-WaVE is a general and flexible zero-inflated…

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t-SNE
Desktop

t-SNE t-distributed Stochastic Neighbor Embedding

A technique for dimensionality reduction that is particularly well suited for…

A technique for dimensionality reduction that is particularly well suited for the visualization of high-dimensional datasets. The technique can be implemented via Barnes-Hut approximations, allowing…

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