Introduction | Install and load the package | Install and check IgBLAST | Install IgBLAST | Check IgBLAST | Install and select an IgBLAST-compatible germline database | Preinstalled germline databases | Install additional IgBLAST-compatible germline databases | Install an IgBLAST-compatible germline database from IMGT/V-QUEST | Install an IgBLAST-compatible germline database from user-supplied gene allele sequences | Select the germline database to use with igblastn() | Internal data and auxiliary data | What are the internal data and auxiliary data? | IgBLAST-provided internal/auxiliary data | igblastr-generated internal/auxiliary data | How is this data generated? | How to use the igblastr-generated internal/auxiliary data with igblastr? | Select a constant region database (optional) | Use igblastn() | Prepare the query sequences | Call igblastn() on the query sequences | Downstream analysis | Distribution of percent mutation across BCR sequences | Distribution of germline genes | Lengths and motifs of CDR3 sequences | Advanced usage | Passing additional arguments to igblastn() | Restrict the search to a subset of user-supplied gene alleles | Combine germline databases from two different organisms | Create the hybrid germline database | A quick look at columns v_call, d_call, and j_call | A TCR analysis example | Prepare the TCR query sequences | Install a TCR germline database | Select a TCR constant region database (optional) | Call igblastn() on the TCR query sequences | Future developments and session information | Future developments | Session information

1 Introduction | 2 HOWTOs | 3 Session Information

Brief Recap | XString objects | XStringSets | XStringViews | Summary | Low-Level Matching | Edit Distance | Simple Matching | Fixed Pattern Matching | matchPattern | countPattern | One Pattern, Multiple Subjects | Matching with PDicts | What is a PDict? | Exact Matching | Trusted Bands | Inexact Matching | PDict Matching Without a PDict | Performance Notes | Other Matching Utilities | Finding Mismatches | Finding Coverage | Biological Applications | Finding Palindromes | Finding Ampilicons for a Primer Pair | Position Weight Matrix (PWM) Matching | Further Reading | Session info

Introduction | Creation and masking | Analytic utilities | Exporting to file | Session Information

Introduction | Install and load the package | ZarrArray objects | Construction | Array and matrix operations | Other operations | Write an array-like object to disk in Zarr format | Session information

Introduction | Install and load the package | A quick overview of the functionality available in the package | Explode CIGAR strings | Tabulate CIGAR operations | Calculate the number of positions spanned by a CIGAR | Trim CIGAR strings along the reference or query space | Turn CIGAR strings into ranges of positions | Project positions from query to reference space and vice versa | Project sequences from one space to the other | Session information

What is S4? | The S4 class system | A different world | S4 in Bioconductor | S4 from an end-user point of view | Where do S4 objects come from? | How to manipulate S4 objects? | How to find the right man page? | Inspecting objects and discovering methods | Implementing an S4 class (in 4 slides) | Class definition and constructor | Getters | Extending an existing class | Slot inheritance | Method inheritance | Incremental validity method | What else?

1 Introduction | 2 Functionality for all existing organisms | 3 Seqinfo objects | 4 Examples | 5 Session Information

Introduction | Install and load the package | The Seqinfo constructor | Seqinfo accessors | Operations on Seqinfo objects | Subset by seqnames | Rename, drop, add and/or reorder the sequences | Merge Seqinfo objects | Seqinfo objects as parts of higher-level objects | Session information

Introduction | Install and load the required packages | The test datasets | Sparse vs dense representation | TENxMatrix vs HDF5Matrix objects | Bring the sparse dataset in R | Bring the dense dataset in R | Create the test datasets | Block-processed normalization and PCA | Code used for normalization and PCA | Block processing and block size | Monitoring memory usage | Normalization and PCA of the 27,998 x 12,500 test dataset | Normalization | TENxMatrix (sparse) | HDF5Matrix (dense) | HDF5Matrix as sparse | On-disk realization of the normalized datasets | PCA | Comprehensive timings obtained on various machines | Timings for DELL XPS 15 laptop | Timings for Supermicro SuperServer 1029GQ-TRT | Timings for Apple Silicon Mac Pro | Timings for Intel Mac Pro | Discussion | TENxMatrix (sparse) vs HDF5Matrix (dense) | Hybrid approach | A note about memory usage | Main takeaways | Session information

Introduction | Installation | The Array virtual class | The extract_array() generic function | Block processing of array-like objects | Other functionalities | Session information

Introduction | Install and load the package | The h5mread() function | Basic example | An example involving sparse data | A note about COO_SparseArray objects | Other functionality provided by the h5mread package | h5dim() and h5chunkdim() | Utility functions to manipulate the dimnames of an HDF5 dataset | H5File objects | Session information

Introduction | Install and load the package | The SparseArray virtual class and its two concrete subclasses | SVT_SparseArray objects | Construction | SVT_SparseArray vs COO_SparseArray | The SparseArray API | The core array API | type() and is_sparse() | is_nonzero() and the nz*() functions | Subsetting and subassignment | Summarization methods (whole array) | Operations from the Arith, Compare, Logic, Math, Math2, and Complex groups | The 2D API | SVT_SparseMatrix objects | Transposition | Combine multidimensional objects along a given dimension | matrixStats methods | rowsum() and colsum() | Matrix multiplication and cross-product | Other operations | Generate a random SVT_SparseArray object | Read/write a sparse matrix from/to a CSV file | Comparison with dgCMatrix objects | "SVT layout" vs "CSC layout" | Working with a big sparse dataset | Learn more | Session information

1. Motivation | 2. Using the 2bit C library in the C code of your package | Find the header files | Compile and link against the library | Notes | 3. R functions defined in Rtwobitlib

Introduction | Installation | Functions defined in the package | list_UCSC_genomes() | get_UCSC_chrom_sizes() | list_UCSC_tracks() | fetch_UCSC_track_data() | UCSC_dbselect() | Session information

Motivation | HTSlib version | Use | Find headers | Compile and link against the library | Implementation notes

Introduction | Out-of-sync objects | The updateObject() generic function | A tedious process | updateBiocPackageRepoObjects() | List of tools provided by the updateObject package | Session information

Introduction | GRanges: Genomic Ranges | Splitting and combining GRanges objects | Subsetting GRanges objects | Basic interval operations for GRanges objects | Interval set operations for GRanges objects | GRangesList: Groups of Genomic Ranges | Basic GRangesList accessors | Combining GRangesList objects | Basic interval operations for GRangesList objects | Subsetting GRangesList objects | Looping over GRangesList objects | Interval overlaps involving GRanges and GRangesList objects | Finding the nearest genomic position in GRanges objects | Session Information

Motivation and challenges | Memory footprint | RleArray and HDF5Array objects | Hands-on | DelayedArray/HDF5Array: Future developments

Introduction | Implementing the seed class | Class definition | Constructor | The seed contract | dim() and dimnames() | extract_array() | What to import? | Testing | Implementing high-level classes ADSArray and ADSMatrix | ADSArray class definition | The ADSArray() constructor | ADSMatrix class definition | Going from ADSArray to ADSMatrix | Going from ADSMatrix to ADSArray | Implementing optimized backend-specific methods | What to export?

Recent additions to package DelayedArray | Recent additions to package HDF5Array | Work in progress and future work

Introduction | Installation | Basic usage | Using forgeBSgenomeDataPkgFromNCBI() | Using forgeBSgenomeDataPkgFromUCSC() | Final steps | sessionInfo()

Introduction | Vector-like and list-like objects | Vector-like objects | Subsetting a vector-like object | Concatenating vector-like objects | Looping over subsequences of vector-like objects | List-like objects | Vector Annotations | Session Information

Introduction | Installing the txdbmaker package | Using makeTxDbFromUCSC | Using makeTxDbFromBiomart | Using makeTxDbFromEnsembl | Using makeTxDbFromGFF | Saving and Loading a TxDb Object | Using makeTxDbPackageFromUCSC and makeTxDbPackageFromBiomart | Session Information

Introduction | How to forge a BSgenome data package with bare sequences | How to forge a BSgenome data package with masked sequences | Session information

Introduction | Pairwise Sequence Alignment Problems | Main Pairwise Sequence Alignment Function | Pairwise Sequence Alignment Classes | Pairwise Sequence Alignment Helper Functions | Edit Distances | Application: Using Evolutionary Models in Protein Alignments | Application: Removing Adapters from Sequence Reads | Application: Quality Assurance in Sequencing Experiments | Computation Profiling | Computing alignment consensus matrices | Exercise Answers | Session Information

Introduction | Installing the GenomicFeatures package | Obtaining a TxDb object | Retrieving Data from a TxDb object | Pre-filtering data based on Chromosomes | Retrieving data using the select() method | Methods for returning GRanges objects | Working with Grouped Features | Predefined grouping functions | Getting the actual sequence data | Session Information

Overview | Using probe packages | Basic functions | Reverse and complementary sequence | Matching sets of probes against each other | Base content | Relating to the features of an AffyBatch | Some sequence related "preprocessing and quality" plots

The Biostrings-based genome data packages | Finding an arbitrary nucleotide pattern in a chromosome | Finding an arbitrary nucleotide pattern in an entire genome | Some precautions when using matchPattern | Masking the chromosome sequences | Hard masking | Injecting known SNPs in the chromosome sequences | Finding all the patterns of a constant width dictionary in an entire genome | Session info

Introduction | Anatomy of a SummarizedExperiment | Assays | 'Row' (regions-of-interest) data | 'Column' (sample) data | Experiment-wide metadata | Constructing a SummarizedExperiment | Top-level dimnames vs assay-level dimnames | Common operations on SummarizedExperiment | Subsetting | Getters and setters | Range-based operations | Interactive visualization | Session information

Background | Support for existing organisms | File format for new organism | Example File | Contacting us with your new file

GRanges objects | GRangesList objects | Other resources

Motivation | Deriving a simple class | Overview | Defining the class and its constructor | Defining a validity method | Defining a getter method | Some comments on package organization | Deriving a class with custom slots | Class definition | Defining the constructor | Creating getter methods | For 1D data structures | For 2D data structures | For SummarizedExperiment slots | Defining the validity method | Creating a show method | Creating setter methods | Other types of modifying functions | Enabling subsetting operations | Getting a subset | Assigning a subset | Defining combining methods | By row | By column | Defining coercion methods | Coercion from SummarizedExperiment | Deriving from a RangedSummarizedExperiment | Unit testing procedures | Constructor | Getters | Setters | Other modifying functions | Subsetting methods | Combining methods | Documentation | Session information

1 Introduction | 2 IRanges objects | 3 Vector Views | 4 Lists of Atomic Vectors | 5 Session Information

1 Introduction | 2 The GenomicRanges abstraction | 3 Formalizing mcols: Extra column slots