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.

mass-cytometry dataset, UMAP visually revealed 8 major cell clusters (Figure 2A). One was composed of all B cell subsets (and close to a small cluster of plasma cells) and one of all T cell subsets. Four small homogeneous clusters corresponded to macrophages, NK cells, eosinophils and non-classical monocytes. The last cluster contained 11 out ...

除了之前说过的三种常见单细胞基因可视化方法外，还有一种最常用的就是直接在 umap 或者 tsne 降维图上显示表达某基因的细胞，这种方式更加直观，但是只能显示一个基因，一般用于标记重要的基因。

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...

UMAP (Uniform Manifold Approximation and Projection) 算法是一种创新的降维流形学习算法。 来自于拓扑数据分析。 可以用于类似于 t-SNE 的可视化，但也可以用于一般的非线性降维。 文章里的这个图可以看出， sars-cov-2 感染患者的血清 组学数据 与健康个体的组学数据得到了很好的分辨，而其他组则表现出一定程度的分离。 注：示例数据仅作展示用，无实际意义！ 很显然，重点在于umap分析，可视化只是常见的散点图。 #n_neighbors 用似的局部邻域的大小(根据邻域 …

2023年7月19日 · 降维算法：在单细胞转录组生信分析中，常见的降维算法有两种，umap和t-sneumpa运算速度会更快，并且在保留数据结构的同时提供了更好的扩展性。umap的主要步骤学习高维空间中的流形结构找到该流形的低维表示，优化低维图。

2022年10月21日 · In this work, we present the application of UMAP to the analysis of various IFC datasets (including pollen, red blood cells, and monocyte cell line (THP1), demonstrating its ability to facilitate visualization, classification, and tagging of objects from large-scale experiments on complex populations, while working directly on pixel-based image ...

~4 million single-cell transcriptomes from adult mouse brain labeled by source brain region represented by a UMAP (Yao Z. et al. 2023, bioRxiv). What is a UMAP? This is a special type of graph, called a Uniform Manifold Approximation and Projection (UMAP). UMAPs are helpful ways of displaying many types of data and are often referred to as one ...

2021年5月3日 · We introduce j-SNE and j-UMAP as their natural generalizations to the joint visualization of multimodal omics data. Our approach automatically learns the relative contribution of each modality to a concise representation of cellular identity that promotes discriminative features but suppresses noise.

2021年4月12日 · UMAP (Uniform Manifold Approximation and Projection) 算法是一种创新的降维流形学习算法。 来自于拓扑数据分析。 可以用于类似于 t-SNE 的可视化，但也可以用于一般的非线性降维。 文章里的这个图可以看出， sars-cov-2 感染患者的血清组学数据与健康个体的组学数据得到了很好的分辨，而其他组则表现出一定程度的分离。 注：示例数据仅作展示用，无实际意义！ 很显然，重点在于umap分析，可视化只是常见的散点图。 umap <- …