Package: GeneTrackR 0.99.2

Introduction | Installation | Load GeneTrackR | Locate the bundled example data | Read the three core inputs | Inspect a candidate gene | Retrieve variants for the same locus | Build gene haplotypes | Test a phenotype association | Where to go next | Session information

Introduction | Installation | File inventory | Core dimensions | Coordinate conventions | Load representative objects | GeneA haplotype truth | Phenotype truth and controls | LD truth | RNA-seq and Ribo-seq signal truth | Recommended use in examples and tests | Session information

Introduction | Installation | Load the canonical demo inputs | Object contracts used in the workflow | Annotation and feature retrieval | Variant retrieval | GeneA haplotypes | Haplotype-phenotype association | Single-variant phenotype association | Linkage disequilibrium | Phenotype-guided haplotype refinement | Variant-effect prioritization | Session information

Introduction | Installation | Supported formats and coordinate conventions | Load the deterministic annotation files | Annotation object contract | Validate and summarize annotations | Retrieve genes, transcripts, and regions | Exact gene or transcript retrieval | Genomic-region retrieval | Retrieve a flat table | Convert annotations and expose standardized tables | Merge compatible annotations | Write annotations and perform round-trip checks | GenePred / GenePredExt | GTF / GFF3 | BED6 / BED12 | Visualize annotation structure | Gene model | Transcript structure | Genomic region | Interval feature track | Gene-length distribution | Recommended annotation workflow | Session information

Introduction | Installation | Plot a gene | Transcript collapse modes | Plot a transcript | Genomic coordinates | Spliced transcript coordinates | Plot a genomic region | Strand direction | CDS, UTR, and exon geometry | Labels | Highlight an interval | Colors and borders | Choosing the structural view | Session information

Introduction | Installation | Read signal tracks | Lazy versus memory mode | Strand semantics | Retrieve a genomic interval | Bioconductor interoperability | Normalize and merge signals | Bin retrieved signal | Write bigWig output | Plot signal over a gene | Plot signal over a transcript | Ribo-seq reading-frame view | Plot a genomic region | Signal summaries and visual transformations | Integrated track figure | Practical guidance for large signal data | Session information

Introduction | Installation | Read variants | Large indexed VCF files | Validate and summarize | Retrieve by genomic region | Retrieve by gene or transcript | Filter by variant attributes | Plot a variant track | Write a standardized VCF subset | Downstream handoff | Session information

Introduction | Installation | Prepare the track objects | Choose exactly one genomic locator | Gene-centered view | Transcript-centered view and Ribo-seq frames | Explicit multi-gene region | Add feature and variant panels | Multiple independent feature or variant tracks | Layout and panel heights | Styling responsibilities | Large-dataset workflow | Session information

Introduction | Installation | Step 1. Prepare VCF genotypes and annotation | Step 2. Build the primary GeneA haplotypes | Step 3. Inspect the HapVariant object | Step 4. Choose the genotype representation | Allele-string mode | Binary code mode | Step 5. Control missing-genotype filtering | Step 6. Construct transcript, flanking-region, and custom-region haplotypes | Transcript-defined haplotypes | Strand-aware flanking regions | Explicit genomic regions | Sample and variant-type filtering | Step 7. Draw the haplotype-variant figure | Step 8. Pass the same haplotype object downstream | Session information

Introduction | Installation | Step 1. Prepare phenotype and genotype inputs | Step 2. Summarize phenotype quality and distributions | Step 3. Verify sample matching explicitly | Step 4. Test the primary haplotype-phenotype association | Step 5. Compare traits and choose the statistical settings | Step 6. Control phenotype-association plot appearance | Step 7. Test a single variant against phenotype | Step 8. Pass the same objects downstream | Session information

Introduction | Installation | Step 1. Prepare VCF genotypes and annotation | Step 2. Compute the primary twelve-variant LD-gradient example | Step 3. Inspect the LDTrack object and pairwise statistics | Step 4. Inspect the LD matrix and quantify the LD gradient | Step 5. Draw the triangular LD heatmap | Step 6. Add gene structure and natural-variant markers | Step 7. Compare the LD-gradient, low-LD, and two-variant regions | Step 8. Control samples, variant types, LD methods, and genotype retention | Select samples | Select variant types | Retain the dosage matrix when needed | Use D-prime cautiously | Step 9. Interpret LD and pass the selected region downstream | Session information

Introduction | Installation | Step 1. Prepare the original haplotypes and phenotype data | Step 2. Inspect genotype similarity and phenotype correspondence before refinement | Step 3. Refine haplotypes using protein_content | Step 4. Inspect the HapRefined object | Step 5. Inspect pairwise tests and merge decisions | Step 6. Plot the refined haplotype structure | Keep the original haplotypes inside refined blocks | Collapse each refined group to one row | Step 7. Plot phenotype distributions after refinement | Step 8. Evaluate trait choice and refinement thresholds | A strongly haplotype-associated trait may preserve all groups | A negative-control trait can collapse all groups | Multiple traits make the refinement criterion stricter | Step 9. Interpret and reuse refined haplotypes | Session information

Introduction | Installation | Step 1. Prepare GeneA variants and phenotype data | Step 2. Understand genotype coding before interpreting effect direction | Step 3. Calculate the primary protein-content effect scan | Step 4. Inspect the result object | Step 5. Rank candidate variants | Step 6. Interpret tied effects together with genotype structure and LD | Step 7. Inspect signed effects carefully | Step 8. Validate varA03 with a direct single-variant phenotype plot | Step 9. Compare multiple traits and connect downstream evidence | Session information

Introduction | Step 1. Define and read the inputs | Step 2. Validate and summarize the core objects | Step 3. Inspect the locus in a browser-like view | Step 4. Retrieve the gene-body variants | Step 5. Construct and visualize the GeneA haplotypes | Step 6. Test phenotype associations | Step 7. Inspect the regional LD gradient | Step 8. Refine haplotypes with phenotype evidence | Step 9. Rank variant effects and integrate the evidence | Step 10. Export results and scale the workflow to real datasets | Installation | Session information

Introduction | Step 1. Prepare output directories and representative objects | Step 2. Export genomic track files | Annotation tracks | Signal tracks | Variant tracks | Step 3. Save figures as PDF and PNG | Step 4. Export analysis tables | Step 5. Export the LD matrix cleanly | Step 6. Optionally collect tables in an Excel workbook | Step 7. Save complete GeneTrackR objects with RDS | Step 8. Record provenance and verify the export | Installation | Session information