Single-cell transcriptome sequencing (sc-RNA-seq) experiments allow us to discover new cell types and help us understand how they arise in development. The Monocle 3 package provides a toolkit for analyzing single-cell gene expression experiments.

Monocle 3 can help you perform three main types of analysis:

  • Clustering, classifying, and counting cells. Single-cell RNA-Seq experiments allow you to discover new (and possibly rare) subtypes of cells. Monocle 3 helps you identify them.
  • Constructing single-cell trajectories. In development, disease, and throughout life, cells transition from one state to another. Monocle 3 helps you discover these transitions.
  • Differential expression analysis. Characterizing new cell types and states begins with comparisons to other, better understood cells. Monocle 3 includes a sophisticated, but easy-to-use system for differential expression.

Under construction

Monocle 3 is currently in the beta phase of its development. This means there are likely bugs and performance issues that will need to be addressed. We are working hard towards a stable release, but please be patient while Monocle 3 is under construction.

The documentation on this page is also still under construction. Not all features currently implemented have been completely documented.

For more information on the algorithms at the core of Monocle, or to learn more about how to use single-cell RNA-Seq to study complex biological processes, explore our publications.

Before we look at Monocle 3's functions for each of these common analysis tasks, let's see how to install Monocle.

Previous Next