Cell classification from dual fluorescence labels

Brief Introduction

Cells are automatically identified and coded based on the nuclear stained channel. Then cells are classified according to the expression of two other molecular markers to give the table  “Marker 1 positive”, “Marker 2 positive”, or “Marker 1 and 2 dual positive”. At the end, the cell number in each category is summarized.

#Examples 

tissue section of mice (courtesy from Dr. Chiang CK)

#Description

Classify cells with different expressing profiles. The mask images from molecule staining channels are generated by autothreshold Otsu and MaxEntropy methods or by user definalbe interface. Then the ROI are applied on the mask images to classify cells with different exprssion patterns.

Instruction

The nucleus are identified by the trained machine learning model from Weka. The positive signal for the molecular markers can be defined by autothreshold Otsu, MaxEntropy, or user-interacting methods. Two result tables will be given. One carries the information of each cell while another one brings the summary result at the end.

How to cite

If this helps your assay in your research, please cite the doi of this tool.