## Find insights with a flexible, intuitive notebook

Assemble analyses with Python, text, table viewers, and no-code chart cells on a familiar notebook canvas. Use Markdown to weave narrative and computation, while rendering interactive dataframes, Plotly figures, or static images—all in one document.

## Build interactive interfaces with input widgets

Latch Plot features an intuitive, immediate-mode GUI library for creating interfaces. Bind UI to Python with simple inline calls and automatically trigger downstream updates when inputs change. Experiment with inputs effortlessly and reuse notebooks for future datasets with ease.

## Scale seamlessly for intensive omics analyses

Easily run intensive omics workflows like single-cell or ATAC-seq. Plots lets you instantly scale your notebook's resources—up to 8 GPUs, 2 TiB of RAM, and 96 CPUs—to handle even the most demanding tasks.

## Your Scientific and Programming Assistant

Write code, create visualizations, fix bugs, assemble interactive applications, and kickstart whole analyses - all from a prompt.

See it in action:

- Combine metadata and counts files  
  Bring count files files from anywhere and combine with metadata from Registry into a single AnnData object

- Subset, filter, and perform QC  
  Subset the AnnData object according to patient ID and tissue types, filter cells with low quality, and perform quality control

- Normalize, reduce dimensions, and preview  
  Normalize the data and reduce the dimensions of the AnnData object using Scanpy and visualize the results

- Annotate and subcluster  
  Install CellTypist, annotate the AnnData object, and subcluster the data

- Retrieve and visualize marker genes  
  Retrieve and visualize marker genes for T cell subtypes

## Handoff interactive reports to customers

Create white labeled reports for customers to visualize their results.