Introduction | Preparation | Sketch cells | Principal component analysis (PCA) | t-SNE | UMAP | Clustering | Session info

Introduction | Installation | Preparation | Subsampling | Diagnostic plots | Session info | References

Basic workflow | Creating a data set | Calculating performance scores | Preparing performance object for plotting | Plotting | Modifications to the basic workflow | Stratification | Modification of plots | Custom color assignment | Interactive exploration | Session info

Introduction | Installation | Usage | Example - single-cell RNA-seq clustering benchmark | Programmatic interface | Exporting data from the app | Additional examples | Session info

Overview | What's New in Version 1.6.0 | Server Mode for JSON Uploads | JSON Serialization | Browser localStorage Caching | Cache Versioning | URL Parameters for Programmatic Loading | Server Mode Basics | Starting a Server | What Happens When You Start Server Mode | User Interface | Creating JSON Files | From Data Frames | From Existing SummarizedExperiment | Reading JSON Files | Two Loading Methods | Load from URL (jsonUrl) | Load from File Path (jsonFile) | Browser Cache Management | How Caching Works | Manual Cache Control | Clear Cache Button | Cache Versioning (Administrators) | Setting Up Versioning | Version String Format | User Experience | Session info

Introduction | Processing Multiplexed Assays of Variant Effect data | Read composition specification | Filtering | Processing TRANS data | Processing CIS data | Processing TRANS data with primers | Combining samples | Collapsing count matrix to amino acids | Diagnostic plots | Calculating fitness scores | Scoring mutations with edgeR or limma | FAQ | Can digestFastqs process a sample where the reads are spread across multiple (pairs of) FASTQ files? | Session info

Introduction | Installation | Assumed output directory structure | Check that all required alevin files are available | Generate QC report | Create shiny app | Generate individual plots | Session info | References

Introduction | Installation | Preparation | Differential abundance (DA) analysis | Load and visualize example data | Aggregate counts for internal nodes | Perform differential analysis for leaves and nodes | Find candidates | Select the optimal candidate | Differential state (DS) analysis | Additional examples | Session info | References

Introduction | Interface | Examples | Example 1 | Example 2 | Example 3 | Exporting data from the app | Session info

Introduction | The phyloCompData class | A sample workflow | Phylogenetic Tree | Condition Design | Simulating data | Performing differential expression analysis | Comparing results from several differential expression methods | Using your own data | Providing your own differential expression code | The extended data object | The evaluation metrics | Session info | References

Introduction | The compData class | A sample workflow | Simulating data | Performing differential expression analysis | Comparing results from several differential expression methods | The graphical user interface | Direct command-line call | Using your own data | Providing your own differential expression code | The format of the data and result objects | The data object | The result object | The evaluation metrics | ROC (one replicate/all replicates) | AUC | Type I error | FDR | FDR as a function of expression level | TPR | False discovery curves (one replicate/all replicates) | Fraction/number of significant genes | Overlap, one replicate | Sorensen index, one replicate | MA plot | Spearman correlation | Score distribution vs number of outliers | Score distribution vs average expression level | Score vs 'signal' for genes expressed in only one condition | Matthew's correlation coefficient | Session info | References

Why deploying ExploreModelMatrix on a Shiny server? | How to deploy ExploreModelMatrix | Step 1: Setting up the Shiny Server | Step 2: setup ExploreModelMatrix | Installing ExploreModelMatrix | Setup ExploreModelMatrix on the server | ExploreModelMatrix at the IMBEI | Session info

Introduction | Data preparation | Report generation | Generation of individual figures | Input data format | Session info

Introduction | Evaluation | Result visualization | Using a reduced dimension representation as the reference space | Computational efficiency | Session info | References

Installation | Building a genome index | Aligning reads to the genome index | Miscellaneous helper functions | Session info | References