Multiplexed tissue imaging provides deep insight into the composition, organization, and phenotype of normal and diseased tissues. MCMICRO converts these multiplexed images into single-cell data using state of the art algorithms. Single-cell resolution images provide spatial context of the cellular microenvironment and can be used alongside additional profiling methods like scRNA-Seq to make robust biological conclusions.
MCMICRO is an open source, community supported software that uses Docker and workflow software to create pipelines for analyzing microscopy-based images of tissues. MCMICRO processes data sequentially using algorithms (modules) developed in different research groups.
High-plex tissue imaging is a new interdisciplinary field involving a wide range of imaging technologies, and the best image analysis approach is not always clear. MCMICRO implements a “multiple choice” approach that allows users to select different modules for customized image processing.
Modules are being added to MCMICRO incrementally by a diverse developer community seeded by the NCI Human Tissue Atlas Network. See what modules we are currently using, view our growing community, or get help.
MCMICRO comes with a growing library of imaging data (EMIT data) for testing your test run or for developing new algorithms. There is a lot of unexplored biology in the test data as well!
MCMICRO works with any image that meets the BioFormats standard, most commonly OME-TIFF. These images can be acquired using a wide range of technologies- CODEX, CyCIF, mIHC, mxIF, IMC or MIBI.