CyLinter is quality control software for identifying and removing cell segmentation instances corrupted by optical and/or image-processing artifacts in multiplex microscopy images. The tool is interactive and comprises a set of modular and extensible QC modules instantiated in a configurable Python Class object. Module results are cached to allow for progress bookmarking and dynamic restarts.

CyLinter development is led by Greg Baker at the Laboratory of Systems Pharmacology, Harvard Medical School.

Funding: This work was supported by the Ludwig Cancer Research and the Ludwig Center at Harvard (P.K.S., S.S.) and by NIH NCI grants U2C-CA233280, and U2C-CA233262 (P.K.S., S.S.). Development of computational methods and image processing software is supported by a Team Science Grant from the Gray Foundation (P.K.S., S.S.), the Gates Foundation grant INV-027106 (P.K.S.), the David Liposarcoma Research Initiative at Dana-Farber Cancer Institute supported by KBF Canada via the Rossy Foundation Fund (P.K.S., S.S.) and the Emerson Collective (P.K.S.). S.S. is supported by the BWH President’s Scholars Award.

Project Website: https://labsyspharm.github.io/cylinter/