Changes in version 0.9.0 (2026-10-16)                  

  - Initial CRAN submission.

Reading and storage

  - read_vcf() reads plain or gzip-compressed VCF files (including large
    DiscoSnp-RAD output) into a VCFArrow S4 object. Variant information
    is kept in memory; genotypes are written to disk as an 'Apache
    Arrow' dataset in chunks and read lazily, so datasets larger than
    memory can be processed.
  - set_vcf_groups() assigns samples to groups (populations); vcf_copy()
    makes an independent copy; vcf_gc() deletes the on-disk data of
    objects that are no longer referenced.
  - vcf_memory_estimate() estimates the memory an export needs, and
    vcf_suggest_chunk_size() suggests a chunk size for read_vcf() for
    the available memory.

Filtering, subsetting and merging

  - Variant filters: vcf_filter_quality(), vcf_filter_pass(),
    vcf_filter_biallelic(), vcf_filter_indels(), vcf_filter_coverage(),
    vcf_filter_maf(), vcf_filter_hets(), vcf_filter_missingness(),
    vcf_filter_invariant(), vcf_filter_oneSNV() and
    vcf_filter_multiSNV() (SNV blocks), and, for DiscoSnp-RAD data,
    vcf_filter_rank(), vcf_filter_rpt() and vcf_filter_paralogs().
  - Sample filters and subsets: vcf_filter_missing(),
    vcf_extract_samples(), vcf_extract_groups(), vcf_sub_SNVs() and
    vcf_sub_SNVs_stratified().
  - vcf_filter_adr() corrects or removes genotypes with an extreme
    allele depth ratio (ALT / (REF + ALT)): they are changed to
    homozygous or set to missing.
  - vcf_bind() merges objects with the same or different samples,
    matching variants by CHROM, POS, REF and ALT, in "intersect" or
    "union" mode, with an ingroup/outgroup mode (outgroup = TRUE) and
    optional recovery of previously filtered loci (recover_loci = TRUE).
    vcf_bind_sparse() is a deprecated alias of vcf_bind(...,
    recover_loci = TRUE).

Statistics and plots

  - vcf_stats() computes per-sample statistics (heterozygosity, missing
    data, depth) and, optionally, Watterson's theta and nucleotide
    diversity per group (vcf_theta()), accumulated chunk by chunk with
    little memory.
  - assess_vcf_missing_data() writes a table and plots of missing data
    per sample, and assess_vcf_coverage() plots of read depth per sample
    (PDF, PNG and SVG).

Writing and conversion

  - write_vcf() writes plain or gzip-compressed VCF files.
  - Converters to the input formats of population-genetic and
    phylogenetic software: vcf2admixture(), vcf2apparent(),
    vcf2arlequin(), vcf2bayesass(), vcf2bayescan(), vcf2eigenstrat(),
    vcf2fasta(), vcf2fineradstructure(), vcf2genepop(), vcf2migrate(),
    vcf2nexus(), vcf2plink_bed(), vcf2plink_ped(), vcf2related(),
    vcf2smartsnp(), vcf2snapp(), vcf2snmf(), vcf2structure() and
    vcf2treemix(); vcf2gt_long() writes a long genotype table (CSV,
    feather or Parquet) and vcf2genlight() returns an 'adegenet'
    genlight object.

Performance

  - vcf_set_workers() runs the per-chunk work of reading, filtering,
    statistics, merging and exporting on background R processes. Results
    do not depend on the number of workers.
  - Performance-critical steps (VCF parsing, per-sample counts, theta
    and pi, writers of the exported formats) are implemented in C++.

Dependencies

  - 'adegenet' (for vcf2genlight()) and 'svglite' (for SVG plots) are
    suggested rather than imported; without 'svglite', SVG plots are
    written with R's Cairo device.