Overview | Quick start | Session information

Overview | Quick start | Session information

Introduction | Based on distance matrices | Hierarchical clustering | Affinity propagation | With a fixed number of clusters | $k$-means clustering | Self-organizing maps | Graph-based clustering | Density-based clustering | Two-phase clustering | Obtaining full clustering statistics | Further comments | Session information

Introduction | Computing the silhouette width | Computing the neighborhood purity | Computing per-cluster RMSD | Computing graph modularity | Comparing two clusterings | Bootstrapping cluster stability | Clustering parameter sweeps | Linking clusters | Comparing multiple clusterings | Session information

Introduction | Quick start | Using low-level functions | Finding overlaps | Searching on text | Fetching all data | Flushing the cache | Customizing the database | Creating the custom database | Reading custom files | Contributing custom sets | Session information

Overview | Quick start | More experimental designs | More comparison types | Subsetting samples | More output options | Session information

Overview | Quick start | Multi-batch analyses | With proteomics | Cell type annotation | Session information

Introduction | Quick clustering | Automated PC choice | Detecting correlated genes | Session information

Introduction | Computing feature-level statistics | Making gene symbols unique | Creating a data.frame | Scaling normalization | Median-based normalization | Pooling normalization | Spike-in normalization | Session information

Overview | Finding nearest neighbors | Finding all neighbors within range | Saving indices to disk | Usage in downstream C++ libraries | Extending to new methods | Introduction | In R | In C++ | Session information

Overview | Quick start | Considering directionality | Differential gene set tests | More output options | Session information

Overview | Quick start | Explaining parameters | Gene-level statistics | More output options | Session information

Introduction | Quick start | Writing the template | Representing data inputs | Computing results | Session information

Overview | Quick start | For R administrators | Session information

Overview | For package developers | Setting defaults | Historical comments | Session information

Overview | Linking instructions | Reading matrix data | Enabling parallelization | Comparison to block processing | Session information

Overview | For package developers | Setting up the package | Specifying Python environments | Defining BasiliskEnvironment objects | Populating environments on installation | Using the environments | Basics | Function constraints | Persisting variables across calls | For end users | Troubleshooting known issues | Fine-tuning basilisk's behavior | Using basilisk directly for analyses | Session information

Overview | Worked example | Setting defaults | Session information

Introduction | Quick start | Class-specific methods | Operating on directories | Extending to new classes | Creating applications | Session information

Overview | Quick start | Saving delayed operations | Session information

Background | Setting the access time | Maintaining thread safety | Deleting old caches | Session information

Overview | Quick start | Session info

Overview | For users | For developers | Session information

Overview | For users | For developers | In-memory caching | Session information

Motivation | Quick start | More interesting seeds | Session information

Introduction | Setting up the data | Mocking up a data set | Pre-processing of intensities | Pooling cells together | Estimating transformation parameters | Gating out uninteresting cells | Applying functions to the original data | Normalizing intensities across batches | Counting cells into hyperspheres | Testing for significant differences in abundance | Controlling the spatial FDR | Visualizing and interpreting the results | With static plots | Using a Shiny app | Additional notes | Session information

Overview | Counting single barcodes | Counting combinatorial barcodes | Counting dual barcodes | Counting dual barcodes (single-end) | Counting random barcodes | Further options | Supporting mismatches | Searching the other strand | Parallelization across files | Session information

Overview | Quick start | Available libraries | Using interfaces | Contributing

Overview | Quick start | Session information

Overview | Using the ResidualMatrix | Retaining certain factors | Restricting observations | Session information

Introduction | Reading files | Uploading files | Basic usage | Link generation | Changing permissions | Probational uploads | Inspecting the quota | Validating metadata | Administration | Session information

Overview | Setting up the dataset | Rescaling by neighbors | Intersecting clusters | Multi-metric UMAP | Intersecting graphs | Correlation analyses | Session information

Overview | Finding references | General-purpose references | Human primary cell atlas (HPCA) | Blueprint/ENCODE | Mouse RNA-seq | Immune references | Immunological Genome Project (ImmGen) | Database of Immune Cell Expression/eQTLs/Epigenomics (DICE) | Novershtern hematopoietic data | Monaco immune data | Adding new references | Session information | References

Introduction | Finding datasets | Loading a dataset | Adding new datasets | Session information

Overview | Saving a BumpyMatrix | Loading a BumpyMatrix | Session info

Overview | Quick start | Integration with other objects | Validation | Session information

Overview | Quick start | Quality scaled strings | Session information

Overview | Quick start | Session information

Overview | Quick start | Further comments | Session information

Overview | Matrix multiplication | Other utilities | Caveats | Session information

Motivation | Session information

Overview | Meta-analyses on $p$-values | $p$-value combining strategies | Summarizing the direction | Further comments | Session information

Introduction | Available distributions | Chunking | Further comments | Session information

Introduction | Description of the GInteractions class | Construction | Getters | Setters | Subsetting and combining | Sorting, duplication and matching | Distance calculations | Overlap methods | Linking sets of regions | Finding the bounding box | Enforcing anchor ordering in StrictGInteractions | Description of the InteractionSet class | Other methods | Description of the ContactMatrix class | Sorting and duplication | Distance calculation | Converting between classes | Inflating a GInteractions into a ContactMatrix | Deflating a ContactMatrix into an InteractionSet | Linearizing an InteractionSet into a RangedSummarizedExperiment | Summary

Introduction | Setting up demonstration data | Function organization | Mutual nearest neighbors | Overview | The new, fast method | The old, classic method | The cluster-based method | Batch rescaling | Using data subsets | Selecting genes | Restricted correction | Other utilities | Multi-batch normalization | Multi-batch PCA | Session information | References

Overview | The DeferredMatrix class | The LowRankMatrix class | The ResidualMatrix class | Session information

Overview | Construction | Basic operations | Advanced subsetting | Additional operations | Session information

Overview | MST construction | Operations on the MST | The PseudotimeOrdering class | Session information

Introduction | Documentation | Session information

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Introduction | Obtaining each dataset | Investigating mapping statistics | Session information | References

Motivation | Functions | Example | Session information

Introduction | Creating a TileDBArray | Manipulating TileDBArrays | Controlling backend creation | Session information

Overview | Setting up | Deriving a BatchelorParam subclass | Defining a batchCorrect method | Input | Output | Demonstration | Session information

Overview | Taking the cross-product | Centering and/or scaling | Other SVD-related options | Running the PCA | Session information