Abstract of singIST as a Bioconductor library | Introduction | Version information and reproducibility | Inputs of singIST | Superpathways | Example 1: Superpathway with the same pathway gene set for each cell type | Example 2: Superpathway with different gene sets per cell type (optional) | Human scRNA-seq | Example 1: Dendritic Cells in regulating Th1/Th2 Development | Example 2: Cytokine-Cytokine receptor interaction superpathway | Disease model scRNA-seq | Example: Oxazolone mouse model of Atopic Dermatitis | Fit Optimal asmbPLS-DA and compute validation metrics for the optimal model | Example: fitting cytokine-cytokine receptor interaction and dendritic cells | in regulating | Compute recapitulation metrics | Example: Evaluating Oxazolone mouse model of Atopic Dermatitis for Dendritic | Cells and cytokine superpathways | Offline reproducibility | Appendix: Missing value handling in human pseudobulk matrices | Problem setup | Step 1: Impute the training fold using multiblock MFA. | Step 2: Impute the validation fold by projection (no re-fitting). | Session Info

Overview | Relationship with the Bioconductor ecosystem | How ProteinBatcher differs from msqrob2 | Input data and workflow parameters | Input data | Sample annotation structure | Workflow parameters | The example data set | Example 1: workflow with interaction testing (condition-by-batch) | Accessing the organised effects | Filtering and imputation summary tables | Differential effects: IL13 vs NoTreated | Main effect (all proteins) | Common effect (batch-independent proteins) | Interaction effect (batch-dependent proteins) | Deregulogram: interpreting batch-dependent effects | Example 2: workflow without interaction testing | Session info