MAUI

MAUI performs low-level pre-processing of Multiplexed Mass Based Imaging (MBI) data from technologies such as Multiplexed Ion Beam Imaging by time-of-flight (MIBI-TOF) and Imaging Mass Cytometry (IMC) to remove imaging artifacts and refine multiplexed protein measurements for downstream spatial and phenotypic analysis.

Key Features:

• MBI technology support: Processes data from MIBI-TOF and IMC platforms.
• Background removal: Eliminates background signal to improve detection of true analyte-derived channels.
• Denoising: Performs noise reduction to enhance signal-to-noise ratio in mass-based imaging data.
• Aggregate removal: Identifies and removes antibody aggregates that confound marker quantification.
• Channel crosstalk correction: Corrects overlap between channels to reduce inter-channel interference.
• High-plex protein support: Handles datasets measuring 40 or more proteins per tissue sample.
• Imaging artifact handling: Addresses artifacts arising from sample preparation, assay conditions, and instrumentation.

Scientific Applications:

• Cellular phenotype characterization: Enables more accurate quantification of multiplexed protein markers for in situ cell phenotyping.
• Spatial tissue organization analysis: Improves signal fidelity for analyses of tissue architecture and spatial relationships among cells.
• Research in oncology, immunology, and developmental biology: Provides pre-processed MBI data that support downstream studies in these fields.

Methodology:

Computational steps explicitly include background removal, denoising (noise reduction), aggregate removal including antibody aggregate elimination, and correction of channel crosstalk for MBI datasets (MIBI-TOF and IMC).