Core entities | Sample and assay concepts | Data tables | Registry and analysis | Data organization | Genotype and phenotype | Object structure | File and path references | Further reading

From a manifest to a cohort | A wide table instead | Reading the cohort back | Writing a pipeline sample sheet | Registering an analysis | Saving and loading a cohort | Translating features across species | Where to go next

Core entities | Sample and assay concepts | Data tables | Registry and analysis | Data organization | Genotype and phenotype | Object structure | File and path references | Further reading

Column names | Subject-level metadata (subject_tbl) | Sample mapping columns (sample_map) | Completeness summary columns (completeness_tbl) | Assay type values | Sample ID formats | Object names | R objects and variables | Example object creation | Function names | File names | Package code files | Data files | Example manifest file names | Variable and parameter naming | Documentation and markdown | A quick check before adding something new | Further reading

What can be checked | Pattern mode: is the string well-formed? | Cache mode: does the identifier exist in a snapshot? | Remote mode | Species and version awareness | HGVS variant syntax | Clean a column | Validation framework adapters | Generating test data | Summary

Introduction | Function Overview | Setting up a Shiny App | What gets created? | Example workflow | Using GitHub Templates | Available templates | Tracking Changes | Comparing Multiple Tools | Example use case | Tips and Tricks | Skip confirmations in scripts | Customize after creation | Use with RStudio Projects | Combine functions | Common Questions | Next Steps

Volcano plot | Expression heatmap | Dot plot | UMAP / t-SNE embedding | Shiny usage | Next steps

From a manifest to a cohort | A wide table instead | Reading the cohort back | Writing a pipeline sample sheet | Registering an analysis | Saving and loading a cohort | Translating features across species | Where to go next

Column names | Subject-level metadata (subject_tbl) | Sample mapping columns (sample_map) | Completeness summary columns (completeness_tbl) | Assay type values | Sample ID formats | Object names | R objects and variables | Example object creation | Function names | File names | Package code files | Data files | Example manifest file names | Variable and parameter naming | Documentation and markdown | A quick check before adding something new | Further reading

The one rule | What comes back | The seven statuses | Branching | Building a client | Credentials | Rate limits | Asking many questions at once | One source, not a mix | Supply a throttle | The circuit breaker | Caching | GraphQL | Migrating an existing app | Testing your client

Introduction: The NCBI, entrez and rentrez. | Getting started with the rentrez | Searching databases: entrez_search() | Building search terms | Using the Filter field | Advanced counting | Finding cross-references : entrez_link(): | My god, it's full of links | Narrowing our focus | External links | Using more than one ID | Getting summary data: entrez_summary() | The summary record | Dealing with many records | Fetching full records: entrez_fetch() | Fetch DNA sequences in fasta format | Fetch a parsed XML document | Using NCBI's Web History features | Get a web_history object from entrez_search or entrez_link() | Use a web_history object | Rate-limiting and API Keys | Slowing rentrez down when you hit the rate-limit | What next ?