Building the working tables | The release at a glance | Centers | Organs and cancer types | Assays and data levels | Which assays, at which levels | Who ran what | Multiplexed imaging technologies | Single-cell and spatial coverage | What is ready to analyse | Biospecimens | Clinical variables | What is recorded | How complete it is | Demographics and outcome | Time: longitudinal sampling | Summary | Session information

The data model in brief | Clinical data | The main tables | File components | Identifiers | The grammar | Do not parse the participant out of a file ID | The hierarchy: participant, biospecimen, file | Biospecimens | Files | id_provenance, the lineage table | Worked lineage walks | A Visium spatial transcriptomics object, back to the patient | Comma-separated parents | Descendants of a raw file | A multiplexed imaging cell table | A file from several participants | Pitfalls | Summary | Session information

Choosing a dataset | The question | Finding candidate files | What the metadata say about it | Tracing lineage | Downloading | Reading into a SpatialExperiment | Adding clinical context: a MultiAssayExperiment | Analysis | Quality control | Normalisation | Feature selection and dimensionality reduction | Clustering | What the clusters are | Where to go from here | Notes on reproducibility | Session information

Introduction | Installation | Getting started | What HTAN is | Phase 1 | Phase 2 | How HTAN data are organised | Participants, biospecimens and files | Data levels | Access tiers | Where the data live, and why | What this package does, and what it doesn't | The metadata snapshot | What it is | How it relates to the authoritative sources | A quick tour | Tables and columns | Files | Lineage | Downloading files | Reading and assembling | How these vignettes are built | References | Session information

Introduction | Loading data | Quality control | Normalization | Example analysis | Session information

Creating a MethyLumiSet object from IDATs | Negative and normalization controls | Preprocessing the raw data | Coercions to other data structures | Session information

Finding studies from R | Controlling what getGEO() fetches | Supplementary files | Caching and reproducibility | Private and embargoed records | Where to go next

Know your object | Microarray: limma | RNA-seq counts: DESeq2 / edgeR / limma-voom | Single cell: the OSCA stack | Converting and annotating | Reproducibility | Where to go next

Install | Your first record | The other entity types | Peeking at supplementary files | Where to go next | Getting help

NCBI-computed quantifications vs. submitter files | Checking availability and loading | Why raw counts (and what to do with them) | When you need the submitter's files instead | Where to go next

Why single-cell data is different | The file formats you will meet | Step 1 — inspect: the manifest | Step 2 — decide: loadable units | Step 3 — load | Sample metadata travels with the cells | Full control | The reader dependencies | Working with Seurat | Downstream: the single-cell ecosystem | What is intentionally out of scope | Where to go next

The four GEO entity types | Two file formats, two code paths | SOFT — the complete, verbose record | Series Matrix — the fast, analysis-ready path | Why getGEO() returns different classes | ExpressionSet vs. SummarizedExperiment | Supplementary files: where everything else lives | Where to go next

Introduction | Build reports | Personal build report | Download statistics | Package details | Package Explorer | Dependency graphs | Working with dependency graphs | Graph visualization | Integration with r Biocpkg("BiocViews") | Dependency burden | Identities of maintainers | Provenance

How could I generate a manifest file with filtering of Race and Ethnicity? | How can I get the number of cases with RNA-Seq data added by date to TCGA project with GenomicDataCommons?

What is the GDC? | Quickstart | Installation | Check connectivity and status | Find data | Download data | Metadata queries | Clinical data | General metadata queries | Basic design | Usage | Querying metadata | Creating a query | Retrieving results | Fields and Values | Facets and aggregation | Filtering | Authentication | Datafile access and download | Data downloads via the GDC API | Bulk downloads | BAM slicing | Use Cases | Cases | How many cases are there per project_id? | How many cases are included in all TARGET projects? | How many cases are included in all TCGA projects? | What is the breakdown of sample types in TCGA-BRCA? | Fetch all samples in TCGA-BRCA that use "Solid Tissue" as a normal. | Get all TCGA case ids that are female | Get all TCGA-COAD case ids that are NOT female | Get all TCGA cases that are missing gender | Get all TCGA cases that are NOT missing gender | Files | How many of each type of file are available? | Find gene-level RNA-seq quantification files for GBM | Slicing | Get all BAM file ids from TCGA-GBM | Troubleshooting | SSL connection errors | sessionInfo() | Developer notes

Background | Workflow | Genes and gene details | ssms | convert to VRanges | OncoPrint

Overview of ACME | Getting Started using ACME