scRNA-seq

Using Generative Adversarial Networks to Generate and Augment Single-Cell RNA-seq Data

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Using Generative Adversarial Networks to Generate and Augment Single-Cell RNA-seq Data

Nature Communications 2020 Jan 9 IF: 17.694 Introduction: GAN includes a generator that outputs realistic silicon-generated samples. This is achieved through a neural network that learns to transform a simple low-dimensional distribution into a high-dimensional distribution, which is indistinguishable from the actual training distribution. In this paper, the authors establish a single-cell GAN (scGAN) to … Read more

Novel Graph Neural Network Framework for Single-Cell RNA-Seq

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Novel Graph Neural Network Framework for Single-Cell RNA-Seq

Single-cell RNA sequencing (scRNA-seq) technology enables gene expression detection across the transcriptome within individual cells, which can be used to study somatic clonal structures and characterize cellular heterogeneity in complex diseases. However, the data from scRNA-seq analysis are characterized by complexity, uncertain distributions, large data volumes, and high missing rates, making scRNA-seq analysis for biological … Read more