Single-cell mass spectrometry-based proteomics enables causal inference in observational studies


Single cell proteomics greatly increases the number of replicates and cellular resolution in MS-based proteomic experiments. However, these experiments are expensive (especially when targeting perturbations). Causal inference methods, which are typically challenging to apply to traditional bulk-MS due to the lack of replicates, allow us to estimate the impact of perturbations from purely observational data. We propose a method and workflow for predicting the effect of interventions in observational single cell MS experiments and apply the workflow to a recent observational single cell experiment.

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