cellumap

Cellumap

Cellumap is an open-source software tool for analyzing and visualizing single-cell spatial transcriptomics data. It enables researchers to upload their spatial gene expression data, visualize cell types and states in spatial context, and perform computational analysis.
singlecell transcriptomics visualization analysis

Cellumap: Open-Source Single-Cell Spatial Transcriptomics Analysis Tool

Analyze and visualize single-cell spatial transcriptomics data with Cellumap, an open-source software tool for researchers.

What is Cellumap?

Cellumap is an open-source software application designed specifically for the analysis and visualization of single-cell spatial transcriptomics data. Single-cell spatial transcriptomics is a novel technique that allows researchers to measure gene expression patterns in individual cells while retaining information about the cells' spatial locations within a tissue sample.

Cellumap provides a user-friendly graphical interface to upload spatial gene expression datasets generated by technologies such as 10x Visium. It then constructs customizable 2D spatially-resolved maps of cell types and states based on the gene expression patterns. Researchers can identify cell subpopulations and determine what cell types are located where within the tissue.

The software includes powerful analytical capabilities as well. It enables differential gene expression analysis between user-defined spatial domains. Researchers can also perform trajectory analysis to study biological processes that follow spatial patterns across the tissue section. Cellumap allows extraction of spatial gene expression signatures that distinguish biological conditions.

By combining an intuitive graphical interface with analytical tools tailored for spatial transcriptomics data, Cellumap makes analyzing and visualizing complex spatially-resolved gene expression datasets accessible to a wide range of users. It facilitates biological discovery by revealing tissue organization and specialized cell functionality in health and disease.

Cellumap Features

Features

  1. Visualization of spatial gene expression data
  2. Identification and annotation of cell types and states
  3. Spatial mapping of cell types
  4. Analysis tools like differential expression testing
  5. Integration with Seurat and Scanpy workflows

Pricing

  • Open Source

Pros

Open source and free to use

User friendly graphical interface

Support for multiple spatial transcriptomics assays

Active development and community support

Cons

Limited to spatial transcriptomics, not generic spatial omics

Less analysis functionality than Scanpy or Seurat

Only supports Linux and Mac OSX


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