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Changelog

Source: NEWS.md

HaploBreedR 0.99.1

Initial submission

First release. The package accompanies the manuscript describing haplotype-based breeding decisions in rice.

Superior-haplotype discovery

  • haplobreed_analysis(): single-trait pipeline from GWAS hits or a gene list to a superior haplotype per candidate gene. Builds LD decay and LD regions from the genotype, discovers functional variants (nonsynonymous CDS and UTR) in every tested gene, tests haplotype-trait associations (Student’s t-test / one-way ANOVA, optional PC correction, Tukey and Duncan post-hoc), and applies effect-size, permutation and false-discovery gates. Supports local, MSU7, RAP-DB and Ensembl Plants reference sources.

  • hbr_generate_input_qc_report(): unified input-QC report covering sequence-resource quality, genotype-reference compatibility and individual-ID overlap, written as a text report and three CSV tables.

  • hbr_check_inputs(): pre-flight validation of PLINK files, phenotype records, GFF3 features and sample-ID overlap before launching the full pipeline.

  • hbr_go_enrichment(): GO over-representation per aspect (BP, MF, CC) against the tested-gene universe, with BH-FDR correction.

  • hbr_read_results(): reads the output of haplobreed_analysis() (in-memory result, per-trait output directory, or a named list of either) into a classed hbr_run object. The returned object carries the trait direction, effective gate settings, the PCs used, tested and superior gene lists, functional SNPs per gene, the phenotype table, the publication-style results table, and the pipeline-summary row.

  • hbr_regate(): re-applies the superior-haplotype rule with new thresholds. Accepts either the legacy summary-table input (a data.frame, returned with the significance and superior flags recomputed) or an hbr_run object, in which case all four gates - including the permutation gate and, when stored, the trait threshold - are recomputed and the genes gained or lost versus the stored call are reported.

  • hbr_gene_carriers(): extracts per-individual carrier status of the pipeline’s superior haplotype at a given gene, used to colour prediction-quality panels.

Genomic prediction and breeding decisions

  • hbr_advanced_decision(): multi-trait parent ranking and cross design from one or more haplobreed_analysis() runs. Two-kernel genomic BLUP (VanRaden 2008; Kang et al. 2008) with the pipeline’s superior haplotypes as the feature kernel; honest nested cross-validation with in-fold discovery replay (M0 = GBLUP, M2 = features chosen on all data, M3 = features re-discovered inside each training fold) and a paired comparison of the three (Nadeau and Bengio 2003 corrected t-test plus a paired bootstrap over individuals).

  • hbr_fit_models(): the phenotype-dependent half of the pipeline (loading, GRM, haplotype codes, gate replay, cross-validation, final models, multi-trait index). Returns an hgsi_fit object that can be saved once and reused.

  • hbr_cross_design(): the second half of the pipeline. Consumes an hgsi_fit object, groups superior haplotypes into haplotype blocks, computes cross usefulness (Schnell and Utz 1975; Zhong and Jannink 2007), pyramiding probabilities and required population sizes (Sedcole 1977), and selects a diverse parent set by block coverage with a relatedness ceiling.

  • hbr_cross_plan(): plans any cross between named parents in a decision result - not only the top-ranked ones. Reports which haplotype blocks are fixed, segregating, split between the parents or missing, the exact probability that a doubled-haploid (or RIL) progeny carries every segregating target haplotype, the F2 probabilities, and the number of plants needed to recover at least one carrier at a chosen confidence.

  • Exported modular building blocks: hbr_build_grm(), hbr_reml_two_kernel(), hbr_cross_usefulness(), hbr_pyramid_probability(), hbr_population_size(), hbr_trait_conflicts().

Haplotype blocks

  • hbr_haplotype_blocks(): groups target loci into haplotype blocks. Accepts the original low-level inputs (units, cm_snp, chr_snp) and returns integer block IDs, or a pipeline run (hbr_run), in which case the superior haplotypes are rebuilt, the discovery gate replayed, and a classed hbr_blocks object returned with the block table, per-line carrier matrix and SNP windows. Supports the map-based rules ("recomb", "ld", "either"), the SNP-level methods ("fourgamete", "gabriel") and the two combinations ("recomb+gabriel", "recomb+fourgamete"). Gabriel is implemented with the Gabriel et al. (2002) D’ confidence interval and vectorised pairwise gamete counting.

  • hbr_haplotype_block_table(): the block summary table and the per-locus assignment in one call, for users who want the block table from a low-level locus set without a pipeline run.

Genetic map

  • hbr_rice_genetic_map(): the Nagamura et al. (1997) rice RFLP linkage-map anchors (n approx. 1,650 markers, total 1,510 cM) as a data frame with chr, bp, cm. Interpolated at run time onto the physical positions of any PLINK .bim with a monotone cubic Hermite spline.

Visualisation

Manuscript tables

  • hbr_build_manuscript_tables(): a multi-sheet Excel workbook from a pipeline run, with study summary, gene results, donor tables and breeding decisions.

Reference layer

  • hbr_crop_lookup(): built-in crop-to-species-to-assembly lookup for Ensembl Plants; refreshable against the live FTP listing.

  • hbr_annotate_regions_with_genes() and hbr_read_gff3_genes(): parse a GFF3 annotation and overlap the resulting gene table with a set of genomic regions, labelling each region-gene pair with its relationship (contained, overlaps left/right, contains region).

  • Local, MSU7, RAP-DB and Ensembl Plants reference sources; chromosome names standardised on every slot so they match the genotype convention applied by hbr_normalize_genotype().

S3 methods

  • print(), summary() and plot() methods for the classed results of the pipeline: hbr_run (single-trait discovery), hgsi_fit (fitted genomic prediction models), hgsi_advanced (cross-design result), hbr_regate (re-gated call) and hbr_blocks (haplotype block assignment).

  • print() methods for the reference and QC objects: hbr_reference, hbr_sequence_qc, hbr_compat_report, hbr_id_report and hbr_genotype.

Reproducibility and performance

  • Every run writes pipeline_summary.csv, phenotype_data_used.csv, functional_snps_all_tested_genes.csv, gene_attrition_log.csv and pipeline_result_for_breeding.rds; the RDS carries the gate parameters and the exact phenotype table used, so downstream runs can be replayed without any external state.

  • Genotype reads are streamed through BEDMatrix, so peak memory is one column block rather than the full genotype matrix; the RDS genotype packing is streamed from the same handle.

  • hbr_advanced_decision() records provenance, warnings and the evaluation label per trait (honest_discovery_in_fold, conditional_on_gwas_candidates, conditional_on_discovered_set, approximate_replay).

  • verbose in every function selects a single-line-per-phase console summary; the detailed narration is available by passing verbose = TRUE where noted.