10x Genomics
Chromium Single Cell Gene Expression

Cell Ranger6.4, printed on 11/05/2024

What is Loupe Browser?

Introduction

Loupe Browser is a desktop application that provides interactive visualization functionality to analyze data from different 10x Genomics solutions. Loupe Browser allows you to easily interrogate different views of your 10x Genomics data to quickly gain insights into the underlying biology. Loupe is named for a jeweler's loupe, which is used to magnify and inspect the details of precious gemstones.

Loupe Browser supports the analysis of the following types of data:

Chromium Platform

• 3’ and 5’ single cell gene expression data
• Feature Barcode data including those interrogating cell surface proteins and CRISPR perturbations
• Overlaying V(D)J clonotype information on top of 5’ single cell gene expression data
• Single cell ATAC data
• Single cell Multiome ATAC + Gene Expression data

Visium Platform

• Spatial gene expression data

To use Loupe Browser, open any .cloupe file generated by the Cell Ranger analysis software. The Cell Ranger .cloupe file is embedded with the following information:

• Gene expression information for cells in the sample.
• Various gene expression-based clustering information for the cells, including t-SNE and UMAP projections and differential gene expression.
• Gene annotation information from the transcriptome reference.

Once your data is in Loupe Browser, you can rapidly explore and gain insights from the data without the need to do any programming.

Loupe Browser Single Cell Gene Expression Tutorials

Loupe Browser provides many powerful analysis capabilities. To walk through its features and uses for analyzing your gene expression data, start with the tutorial introduction page.

Loupe Browser is built to accelerate the following applications:

• Finding Cells of Interest
  Use Loupe Browser guided filtering and reclustering tools (versions 5.0 and later) to narrow your focus to the cells that matter.
  

• Finding Significant Genes
  Determine genes that uniquely characterize clusters at the press of a button.
  

• Identifying Cell Types
  Use gene lists and the gene expression view to locate different cell types and functional groups.
  

• Exploring Substructure
  Create custom clusters and use differential expression tools to identify even smaller subgroups in your data.
  

• Exploring Cell Subtypes
  Use the filter panel to create complex boolean filters to find cell subtypes in your dataset.
  

• Integrated Gene Expression and V(D)J Analysis
  Combine gene expression and immune repertoire data from the same sample to gain new insights about complex disease.

• Sharing Results
  Save genes of interest, export data tables, and capture screenshots of your single-cell data.