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 from the community.
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.