Install RegionalST | Preparing your data for RegionalST through BayesSpace | Analysis with the incorporation of cell type proportions | Obtain cell deconvolution proportions | Load example dataset | Identify Regions of Interest (ROIs) with incorporation of proportions | Automatic ROI selection | Manual ROI selection | Draw cell type proportions for the selected ROIs | Perform Cross-regional Differential Analysis with proportions | Perform Cross-regional Cell Type-Specific Differential Analysis with proportions and self-defined regions | Analysis with cell type information | Obtain cell type labels | Identify Regions of Interest (ROIs) with cell type information | Automatic selection of the ROIs | Manual ROI selection with cell type information | Perform Cross-regional Differential Analysis with cell type information | Pathway GSEA analysis based on the cross-regional DEs | Session info

Introduction | Installation and quick start | Install TOAST | How to get help for TOAST | Quick start on detecting cell type-specific differential signals | Example dataset | Estimate mixing proportions | Reference-based deconvolution using least square method | Reference-free deconvolution using RefFreeEWAS | Improve reference-free deconvolution with cross-cell type differential analysis | Improved-RF with myRefFreeCellMix | Improved-RF with use-defined RF function | Partial reference-free deconvolution (TOAST/-P and TOAST/+P) | Choose cell type-specific markers | PRF deconvolution without prior (TOAST/-P) | PRF deconvolution with prior (TOAST/+P) | Complete deconvolution using a geometric approach | Detect cell type-specific and cross-cell type differential signals | Detect cell type-specific differential signals under two-group comparison | Testing one parameter (e.g. disease) in one cell type. | Testing one parameter in all cell types. | Testing one parameter in all cell types by incorporating DE/DM state correlation among cell types | Detect cell type-specific differential signals from a general experimental design | Testing one parameter in one cell type | Testing the joint effect of single parameter in all cell types. | Detect cross-cell type differential signals | Testing cross-cell type differential signals in cases (or in controls). | Testing the overall cross-cell type differences in all samples. | Testing the differences of two cell types over different values of one phenotype (higher-order test). | A few words about variance bound and Type I error. | Variance bound | Type I error | Session info

Installation and quick start | Install caROC | How to get help for caROC | Quick start on evaluating continuous biomarker with covariates adjusted | Illustrating the usage of caROC in details | 1. Covariate-adjusted sensitivity at controlled specificity level (or the reverse) | 1.1 Compute pooled sensitivity at controlled specificed level | 1.2 Sub-population specific sensitivity at controlled specificity level | 2. Covariate-adjusted ROC curve | 2.1 Pooled ROC | 2.2 Sub-population specific ROC | 3. Threshold at controlled sensitivity/specificity for given covariate values