Neuron detection and counting in high-throughput screening images
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Neuron count from cell- based drug screen images Vladimir Morozov, ALS-TDI October , 2014
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Transcript of Neuron detection and counting in high-throughput screening images
Neuron count from cell-based drug screen images
Vladimir Morozov, ALS-TDIOctober , 2014
Cell Profiler pipeline1. Thresholding
2. Nuclei identification
3. Neurite attachment
4. Final neurons
Making training set for detecting healthy neurons
•We consider good looking cells as positive
•Microphages were identified as negative examples•Other non-neuron cells (e.g. astrocytes) were NOT specified as negative
CellProfiler rule-based classifier, ~77% accuracy
IF (Nuclei_Intensity_IntegratedIntensity_ch1 > 6.1516400000000004, [0.36232803790685297, -0.36232803790685297], [-0.80075679385436416, 0.80075679385436416])IF (Neurite_AreaShape_Solidity > 0.52507099999999995, [-0.68639735377870881, 0.68639735377870881], [0.25029235002592609, -0.25029235002592609])IF (Nuclei_Intensity_StdIntensity_ch2 > 0.00113378, [0.11906406640858008, -0.11906406640858008], [-0.65599426031103425, 0.65599426031103425])IF (Neurite_Intensity_StdIntensity_ch1 > 0.0028765700000000002, [0.042546288651953375, -0.042546288651953375], [-0.88894769206543311, 0.88894769206543311])IF (Neurite_Intensity_MassDisplacement_ch1 > 3.5285700000000002, [0.08250012593027499, -0.08250012593027499], [-0.50046974611076089, 0.50046974611076089])
CellProfiler classifier on the picked image
Manually created training set
•We consider good looking cells as positive
•Microphages were identified as negative examples•Other non-neuron cells (e.g. astrocytes) were NOT specified as negative
Built own classifier in R
Using the training set I tried• Yeo-Johnson feature transformation (can
handle negative values) to make them more normally distributed
• 4-5 non-linear (rules, trees, boosting) classifier algorithms
• The best performance ,85% accuracy with the Multivariate Adaptive Regression Splines (MARS,”earth”) algorithm. This model was used for the final neuron classification
Toxic compounds
•Validity of the neuron detection pipeline is confirmed by compounds with the largest cell toxic effect•These compounds are known cytotoxic agents
Protective compounds
•Statically significant protective compounds were identified•These compounds don’t show statistical enrichment for specific pharmacological or structural classes or mechanism of action
