ScBubbletree: computational approach for visualization of single cell RNA-seq data.

ABSTRACT:

Background

Visualization approaches transform high-dimensional data from single cell RNA sequencing (scRNA-seq) experiments into two-dimensional plots that are used for analysis of cell relationships, and as a means of reporting biological insights. Yet, many standard approaches generate visuals that suffer from overplotting, lack of quantitative information, and distort global and local properties of biological patterns relative to the original high-dimensional space.

Results

We present scBubbletree, a new, scalable method for visualization of scRNA-seq data. The method identifies clusters of cells of similar transcriptomes and visualizes such clusters as "bubbles" at the tips of dendrograms (bubble trees), corresponding to quantitative summaries of cluster properties and r

SUBMITTER: Kitanovski S 

PROVIDER: S-EPMC11401305 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature