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Quality Control Software for Multiplex Microscopy.

CyLinter is used to identify and remove noisy single-cell instances in multiplex images of tissue.

pip install GitHub Repo
Tomas Brunsdon via Dribble



QC for Multiplex Microscopy

Although quality control (QC) methods have long been associated with analysis tools for single-cell genomics and transcriptomics research, analogous tools have lagged in the area of quantitative microscopy. There are now at least 9 different multiplex imaging platforms capable of routine acquisition of 20-40 channel microscopy data1,2,3,4,5,6,7,8,9 and each is sensitive to microscopy artifacts. Current tools for microscopy-based QC act on pixel-level data10,11,12,13,14. CyLinter differs in that it allows users to work with both pixel-level and single-cell data to identify and remove cell segmentation instances corrupted by visual and image-processing artifacts that can significantly alter single-cell data quality.

About CyLinter

CyLinter is open-source QC software for multiplex microscopy. The tool is instantiated as a Python Class and consists of multiple QC modules through which single-cell data are passed for serial redaction. Partially-redacted feature tables are cached within and between modules to allow for iterative QC strategies and progress bookmarking. CyLinter is agnostic to data acquisition platform (CyCIF1, CODEX2, MIBI3, mIHC4, mxIF5, IMC6, etc.) and takes standard TIFF/OME-TIFF imaging files and CSV single-cell feature tables as input.

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  14. Baranski, A. et al. MAUI (MBI Analysis User Interface)-An image processing pipeline for Multiplexed Mass Based Imaging. PLoS Comput Biol 17, e1008887 (2021).