CytoGLMM - Conditional Differential Analysis for Flow and Mass Cytometry Experiments
The CytoGLMM R package implements two multiple regression strategies: A bootstrapped generalized linear model (GLM) and a generalized linear mixed model (GLMM). Most current data analysis tools compare expressions across many computationally discovered cell types. CytoGLMM focuses on just one cell type. Our narrower field of application allows us to define a more specific statistical model with easier to control statistical guarantees. As a result, CytoGLMM finds differential proteins in flow and mass cytometry data while reducing biases arising from marker correlations and safeguarding against false discoveries induced by patient heterogeneity.
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flowcytometryproteomicssinglecellcellbasedassayscellbiologyimmunooncologyregressionstatisticalmethodsoftware
5.86 score 3 stars 1 dependents 2 scripts 386 downloadscellpaintr - Perturbation Analysis for Cell Painting Data
This package load cell painting data into R and preprocess feature to make them ready for machine learning. We use random forest to predict cell perturbations from CellProfiler features. We summarize the results in a volcano plot.
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singlecellsoftwareclassificationfeatureextractionpreprocessingvisualization
3.85 score 1 stars 2 scripts