今天的内容讲讲单细胞文章中经常出现的展示细胞marker的图： tsne / umap 图、 热图 、 堆叠小提琴图 、 气泡图 ，每个图我都会用两种方法绘制。 使用的数据来自文献：Single-cell transcriptomics reveals regulators underlying immune cell diversity and immune subtypes associated with prognosis ...

2024年9月9日 · 1．定义：UMAP图是一种基于非线性降维的可视化方式，将高维数据映射到二维或三维空间，并保持数据之间的相对距离和结构，从而使得聚类、异质性和样本间的差异更为明显。 2．用途： （1）单细胞数据分析：UMAP图可以用于单细胞测序数据的降维分析，帮助研究人员探索细胞的状态和细胞间的相似性，从而揭示细胞分化和功能编排的机制。 （2）基因组学和转录组学：UMAP图可以帮助分析高维转录组数据，主要揭示基因库表达与特定生物过程的关 …

2020年10月14日 · Uniform manifold approximation and projection (UMAP) has been rapidly adopted by the population genetics community to study population structure. It has...

2025年1月11日 · 1．定义：UMAP图是一种基于非线性降维的可视化方式，将高维数据映射到二维或三维空间，并保持数据之间的相对距离和结构，从而使得聚类、异质性和样本间的差异更为明显。 2．用途： （1）单细胞数据分析：UMAP图可以用于单细胞测序数据的降维分析，帮助研究人员探索细胞的状态和细胞间的相似性，从而揭示细胞分化和功能编排的机制。 （2）基因组学和转录组学：UMAP图可以帮助分析高维转录组数据，主要揭示基因库表达与特定生物过程的关 …

2023年1月20日 · UMAP is an algorithm that takes a high-dimensional dataset (such as a single-cell RNA dataset) and reduces it to a low-dimensional plot that retains much of the original information. Most, if not all, single-cell RNA sequencing datasets contain thousands of gene expression counts per individual cell.

2024年5月24日 · Principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP) are among the tools life scientists turn to for...

2024年9月27日 · Mugen-UMAP, a Python package, extends the application of UMAP to single-cell DNA sequencing data, focusing on the visualization and identification of cell clusters based on gene mutation information.

2018年12月3日 · Recently, a nonlinear dimensionality-reduction technique, uniform manifold approximation and projection (UMAP), was developed for the analysis of any type of...

PCA, t-SNE, UMAP… you’ve probably heard about all these dimensionality reduction methods. In this series of blogposts, we’ll cover the similarities and differences between them, easily explained! ... Let’s imagine you have a single-cell dataset with the gene expression of 10000 genes across 50.000 cells. For each cell, and for each gene ...

2025年2月25日 · Crescendo directly corrects gene expression. A Harmony batch corrects lower-dimensional embeddings like principal components that are visualized with a 2-dimensional UMAP.B Crescendo extends Harmony to batch correct genes expression, which can similarly be visualized in a UMAP.C Spatial transcriptomics allows for visualization of gene expression in the context of cellular locations.