Using credentials to access S3 buckets | Creating an S3 client

feature and pheno data# | Subsetting the data | Exploratory analysis using boxplots | A note about ggplot2 | Other exploratory analysis | Normalisation | Filtering | Differential expression | Automating the DE analysis | Output as GRanges | Visualisation options | Creating a GEO submission file | Analysing data from GEO | Reading bead summary data into beadarray | Reading IDAT files | Citing beadarray | Asking for help on beadarray

Zarr version | Reading and Writing | Stores | Data Types | Codecs | Compression codecs | Other codecs | Optional fields or features

Introduction | Installation of the HDF5 package | High level R-HDF5 functions | Creating an HDF5 file and group hierarchy | Writing and reading objects | Writing and reading objects with file, group and dataset handles | Writing and reading with subsetting, chunking and compression | Influence of chunk size and compression level | Saving multiple objects to an HDF5 file (h5save) | List the content of an HDF5 file | Dump the content of an HDF5 file | Reading HDF5 files with external software | Removing content from an HDF5 file | 64-bit integers | Low level HDF5 functions | Creating an HDF5 file and a group hierarchy | Writing data to an HDF5 file | Session Info

Introduction | Reading subsets of data | Using the index argument | Using hyperslab selections | Irregular selections | Using hyperslab selection tools | Slowdown when selecting unions of hyperslabs | Summary | Writing in parallel | Example data | Serial writing of datasets | Parallel writing of datasets | Session info

Introduction | Limitations with Rarr | Example data | Quick start guide | Additional details | Working with Zarr metadata | Writing subsets of data | Creating an "empty" array | Updating a subset of an existing array | Appendix | Session info

Public S3 Buckets | Private S3 Buckets | Session Info

Guiding principles | Scope | Zarr version | Functional programming and API design

Introduction | Basic use | Affymetrix data - before preprocessing | Affymetrix data - after preprocessing | ExpressionSet and ExpressionSetIllumina | Two colour arrays, NChannelSet, RGList, MAList | Loading data from ArrayExpress | Making the report more informative by adding a factor of interest | Extended use | Spatial layout of the array | Mapping of the reporters | RNA quality | Session Info | References

Introduction | Data preparation | Module generating functions | Outlier detection | Rendering the report | Session Info

Motivation | Usage | Link to the library | Locating the library headers | Configuration arguments for non-standard system setups | Funding | Session info

beadarray: R classes and methods for Illumina bead-based data | Introduction | Companion packages to beadarray | Citing beadarray | Getting help

beadarray: R classes and methods for Illumina bead-based data | Analysis of Bead-level Data using beadarray} | Citing beadarray | Asking for help on beadarray | Reading bead-level data into beadarray | File formats | A note for those with iScan data | Array annotation | The beadLevelData class | Scan Metrics | Transformation Functions | BASH | Summarization

Introduction | Reading bead-level data into beadarray | Standard Illumina Image Processing} | Alternative Methods | Parallel Processing | References

Motivation | Usage | With rhdf5 | Writing data | Reading data | With external applications | h5dump example | Compiling the compression libraries | Session info

Introduction | Installing and loading the library | Example fit files | Reading files | Working with the data | Records - GPS, speed, altitude, etc | Extracting common data types | Accessing any data type | Example use cases | Plotting a route | Comparing heart rate measurments between devices | More details | Data types and units | Session Info

Introduction | Citing this work | Package installation | Creating a new workflow document | Using RStudio and our template | Working outside RStudio | Converting to LaTeX and PDF | Article upload | R session information | Acknowledgements and funding

Introduction | Data processing | References