haplokit 0.1.13

1|# haplokit 2| 3|Command-line haplotype analysis for indexed VCF/BCF data, with a C++ data plane and Python statistics/plotting layer. 4| 5| 6| 7|English | Chinese 8| 9| 10| 11|## Table of Contents 12| 13|- Capabilities 14|- Installation 15|- Quick Start 16|- Haplotype Workflows 17| - Interval or Single-Site Haplotype Calling 18| - Gene Annotation and Haplotype Table Figure 19| - Population Grouping 20| - Geographic Distribution 21| - Haplotype Network 22|- Phenotype Statistics 23|- Other Workflows 24| - BED Batch Processing 25| - Approximate Grouping 26| - Sample Subset and Missing-Call Imputation 27|- Command Reference 28|- Input/Output Formats 29|- Citation 30|- Support 31|- License 32| 33|## Capabilities 34| 35|| Module | Purpose | Typical output | 36|| --- | --- | --- | 37|| view | Extract haplotypes from a genomic interval, single site, gene ID, gene list, or BED file | hapresult.tsv, hap_summary.tsv | 38|| Annotation | Resolve gene selectors and annotate variant positions with gene model context | gff_ann_summary.tsv, annotated haplotype table figure | 39|| Population summary | Count haplotypes by population group | population columns in tables and figures | 40|| Geographic map | Draw haplotype composition at sampling locations | map figure with pie charts and count scale | 41|| Network | Build PopART-style haplotype networks with MSN, TCS, or MJN | network figure with population pies and mutation ticks | 42|| phenotype | Join haplotypes with numeric traits, run pairwise tests, and draw boxplots | phenotype_stats.tsv, phenotype summary TSV, boxplot | 43| 44|## Installation 45| 46|bash 47|pip install haplokit 48| 49| 50|

51|

From Source (Advanced)

52| 53|#### Requirements 54| 55|- Linux/WSL 56|- Python 3.10+ 57|- C++17 compiler 58|- CMake 3.22+ 59|- make 60|- Native libraries for htslib 61| 62|#### Conda/mamba 63| 64|bash 65|mamba install -c conda-forge compilers make cmake libcurl zlib bzip2 xz 66|python -m pip install --no-cache-dir haplokit 67| 68| 69|#### Ubuntu/Debian 70| 71|bash 72|sudo apt-get update 73|sudo apt-get install -y build-essential make cmake zlib1g-dev libbz2-dev liblzma-dev libcurl4-openssl-dev 74|python -m pip install --no-cache-dir haplokit 75| 76| 77|#### From source checkout 78| 79|bash 80|pip install . 81| 82| 83|#### Development install 84| 85|bash 86|pip install -e . 87| 88| 89|#### Custom backend path 90| 91|If the C++ backend is built outside the package, point the CLI to it: 92| 93|bash 94|export HAPLOKIT_CPP_BIN=/path/to/haplokit_cpp 95| 96| 97|#### Troubleshooting linker errors 98| 99|| Error | Install | 100|| --- | --- | 101|| cannot find -lcurl | libcurl / libcurl4-openssl-dev | 102|| cannot find -lbz2 | bzip2 / libbz2-dev | 103|| cannot find -llzma | xz / liblzma-dev | 104|| cannot find -lz | zlib / zlib1g-dev | 105| 106|

107| 108|## Quick Start 109| 110|bash 111|haplokit view data/var.sorted.vcf.gz -r scaffold_1:4300-5000 --output-file out 112| 113| 114|This extracts haplotypes from the region scaffold_1:4300-5000 and writes results to the out/ directory: 115| 116|| File | Meaning | 117|| --- | --- | 118|| out/hapresult.tsv | Haplotype allele pattern and sample accessions | 119|| out/hap_summary.tsv | Haplotype counts and frequencies | 120| 121|## Haplotype Workflows 122| 123|### Interval or Single-Site Haplotype Calling 124| 125|bash 126|# Region mode: group by full allele pattern across the interval 127|haplokit view in.vcf.gz -r chr1:1000-2000 --output-file out 128| 129|# Site mode: group by alleles at a single position 130|haplokit view in.vcf.gz -r chr1:1450 --output-file out_site 131| 132| 133|

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Details

135| 136|Interval selectors group by the full allele pattern across the region. Single-position selectors automatically use site mode. In strict region mode, samples with heterozygous or missing calls are excluded unless --impute is used. 137| 138|

139| 140|### Gene Annotation and Haplotype Table Figure 141| 142|bash 143|# With gene model annotation 144|haplokit view in.vcf.gz -r chr1:1000-2000 --gff genes.gff3 --plot --output-file out 145| 146|# Compact table theme 147|haplokit view in.vcf.gz -r chr1:1000-2000 --gff genes.gff3 --plot --table-theme compact --output-file out 148| 149| 150|

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Details

152| 153|When a GFF3/GTF file is supplied, the figure draws a pyGenomeTracks-style gene model above the table (backbone/introns, CDS, UTR, and a terminal arrow for strand), with SNP ticks and guide lines connecting each variant to its allele column, plus a CDS/UTR/intron legend. Without --gff only the table is drawn. Output also includes gff_ann_summary.tsv. 154| 155|--table-theme selects the table look: detailed (default; square cells with white gridlines) or compact (flat wide cells, flush, shorter header). The gene model is shared by both themes. 156| 157|

158| 159| 160| 161|### Population Grouping 162| 163|bash 164|haplokit view in.vcf.gz -r chr1:1000-2000 -p popgroup.txt --plot --output-file out 165| 166| 167|

168|

Details

169| 170|popgroup.txt is a two-column tab-separated file: 171| 172|text 173|sample population 174|C1 wild 175|C2 wild 176|C13 landrace 177| 178| 179|Population groups are shown as per-haplotype count columns in the output table and as grouped counts in the figure. 180| 181|

182| 183|### Geographic Distribution 184| 185|bash 186|haplokit view in.vcf.gz -r chr1:1000-2000 -p popgroup.txt --geo data/sample_china_geo.txt --plot --output-file out 187| 188| 189|

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Details

191| 192|Coordinate input is tab-separated: 193| 194|text 195|ID longitude latitude 196|C1 116.40 39.90 197|C2 116.40 39.90 198| 199| 200|Use --show-counts to draw sample-count labels at map pie centers, or --hide-counts to keep them hidden. 201| 202|World map example resources are bundled under data/: 203| 204|- sample_world_geo.txt 205|- world_countries.shp, world_countries.shx, world_countries.dbf 206|- data/figure/haplotype_map_world.png 207| 208|

209| 210| 211| 212| 213| 214|### Haplotype Network 215| 216|bash 217|# TCS network (default) 218|haplokit view in.vcf.gz -r chr1:1000-2000 -p popgroup.txt --network --plot --output-file out 219| 220|# Median-joining network 221|haplokit view in.vcf.gz -r chr1:1000-2000 --network --network-method mjn --plot --output-file out 222| 223| 224|| Method | Name | Description | 225|| --- | --- | --- | 226|| tcs | Statistical parsimony network | Templeton, Crandall & Sing (1992) | 227|| msn | Minimum spanning network | Based on Hamming distances | 228|| mjn | Median-joining network | Bandelt et al. (1999) | 229| 230|

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Details

232| 233|Network figures follow PopART conventions: node area reflects haplotype count, pie slices show population composition, edge ticks show mutation steps, and small black vertices indicate inferred intermediates. 234| 235|

236| 237| 238| 239|## Phenotype Statistics 240| 241|### Basic Usage 242| 243|bash 244|haplokit phenotype \ 245| --hapresult out/hapresult.tsv \ 246| --phenotypes phenotype.csv \ 247| --population popgroup.txt \ 248| --trait yield \ 249| --min-hap-size 5 \ 250| --method welch \ 251| --output yield_stats.tsv \ 252| --summary-output yield_summary.tsv 253| 254| 255|### With Boxplot 256| 257|bash 258|haplokit phenotype \ 259| -H data/example_phenotype_haplotypes.tsv \ 260| -P data/example_phenotype.csv \ 261| -p data/popgroup.txt \ 262| -t yield \ 263| -m 4 \ 264| --method welch \ 265| --plot-box \ 266| -F png \ 267| -T "Yield by haplotype and population" \ 268| -b data/figure/phenotype_population_boxplot.png 269| 270| 271| 272| 273|

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Statistical scenarios

275| 276|| Scenario | Grouping used for tests | Pairwise comparison reported | Boxplot annotation | 277|| --- | --- | --- | --- | 278|| No population file, multiple haplotypes | trait x haplotype | All retained haplotype pairs for each trait | Haplotype-pair significance labels | 279|| Population file, multiple haplotypes | trait x population x haplotype | Haplotype pairs inside each population | Within-population haplotype comparisons and between-population comparisons for the same haplotype | 280|| Population file, one retained haplotype | trait x haplotype x population | Population pairs within that haplotype | Between-population labels only | 281|| Multiple traits | Each selected trait is analyzed independently | One result block per trait | Plotting requires exactly one --trait | 282|| Missing phenotype values | Non-numeric or missing values are ignored per trait | Counts reflect only numeric observations | effective_n records the usable sample count | 283|| IQR outlier preprocessing | Optional Tukey IQR k=1.5 within each trait x population x haplotype group | Tests use records remaining after outlier removal | Plot uses the same filtered records; summary records removed counts | 284| 285|

286| 287|

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Pairwise test methods

289| 290|Hypothesis tests use scipy.stats. 291| 292|| --method | Test | Typical use | P-value adjustment | 293|| --- | --- | --- | --- | 294|| welch | Welch two-sample t-test | Default when variances may differ | Bonferroni by default | 295|| student | Student two-sample t-test | Similar variance assumption | Bonferroni by default | 296|| mannwhitney | Mann-Whitney U test | Non-parametric rank comparison | Bonferroni by default | 297|| tukey | Tukey HSD | Multi-group post-hoc comparison | Uses Tukey HSD p-values directly | 298| 299|

300| 301|

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Outlier preprocessing

303| 304|Use --remove-outliers to remove extreme phenotype values before statistics and boxplot rendering: 305| 306|bash 307|haplokit phenotype \ 308| -H out/hapresult.tsv \ 309| -P phenotype.csv \ 310| -t yield \ 311| --remove-outliers \ 312| -o yield_stats.tsv \ 313| -s yield_summary.tsv 314| 315| 316|The rule is Tukey IQR with k=1.5: values outside [Q1 - 1.5 x IQR, Q3 + 1.5 x IQR] are removed. Filtering is performed separately within each trait x population x haplotype group. Groups with fewer than four numeric values are left unchanged. 317| 318|Summary output records preprocessing with: 319| 320|| Column | Meaning | 321|| --- | --- | 322|| raw_count | Numeric values before outlier removal | 323|| raw_min, raw_max | Raw group range before removal | 324|| outlier_removed | Number of removed values in the summary group | 325|| outlier_method | none or iqr | 326|| outlier_iqr_k | IQR multiplier, currently 1.5 when enabled | 327| 328|

329| 330|

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Phenotype output files

332| 333|| File | Content | 334|| --- | --- | 335|| phenotype_stats.tsv | Pairwise comparison rows with group counts, means, standard deviations, ANOVA result, pairwise statistic, raw p-value, adjusted p-value, significance label, and effective_n | 336|| summary TSV (--summary-output) | Per-trait/per-population/per-haplotype summary statistics, including outlier accounting when preprocessing is enabled | 337|| boxplot (--plot-box) | One selected trait visualized with the same filtering, grouping, and comparison logic used by the statistics | 338| 339|

340| 341|## Other Workflows 342| 343|### BED Batch Processing 344| 345|bash 346|haplokit view in.vcf.gz -R regions.bed --output-file out_batch 347| 348| 349|

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Details

351| 352|regions.bed requires at least three tab-separated columns: 353| 354|text 355|chr1 1000 2000 356|chr2 5000 6000 357| 358| 359|Each BED row is processed independently. Output files are named with a region suffix such as _chr1_1000_2000. 360| 361|

362| 363|### Approximate Grouping 364| 365|bash 366|haplokit view in.vcf.gz -r chr1:1000-2000 --max-diff 0.2 --output-file out 367| 368| 369|--max-diff clusters haplotypes that differ at no more than the given fraction of variant positions. For example, --max-diff 0.2 merges haplotypes differing at ≤20% of variant sites. 370| 371|### Sample Subset and Missing-Call Imputation 372| 373|bash 374|haplokit view in.vcf.gz -r chr1:1000-2000 -S samples.list --impute --output-file out 375| 376| 377|samples.list contains one sample ID per line. --impute treats missing genotypes as reference (0/0) to increase sample retention. 378| 379|### Gene ID and Gene List Selectors 380| 381|bash 382|# Single gene ID (requires --gff) 383|haplokit view in.vcf.gz --gene-id Glyma.01G001000 --gff genes.gff3 --output-file out 384| 385|# Gene list file (one gene ID per line) 386|haplokit view in.vcf.gz --gene-list gene_list.txt --gff genes.gff3 --output-file out 387| 388|# With upstream/downstream extensions 389|haplokit view in.vcf.gz --gene-id Glyma.01G001000 --gff genes.gff3 \ 390| --upstream 2000 --downstream 1000 --strand-aware --output-file out 391| 392| 393|## Command Reference 394| 395|### haplokit view 396| 397|text 398|haplokit view <input.vcf.gz|input.bcf> (-r <region> | -R <regions.bed> | -t <targets> | -T <targets.txt> | --gene-id <id> | --gene-list <file>) [options] 399| 400| 401|Selector options (exactly one required): 402| 403|| Option | Description | 404|| --- | --- | 405|| -r, --region | Single region: chr:start-end or chr:pos | 406|| -R, --regions-file | BED file with multiple regions | 407|| -t, --targets | Comma-separated target regions on one chromosome | 408|| -T, --targets-file | File with one target region per line (same chromosome) | 409|| -G, --gene-id | Single gene ID (requires --gff/--gff3) | 410|| -l, --gene-list | File with one gene ID per line (requires --gff/--gff3) | 411| 412|Calling options: 413| 414|| Option | Default | Description | 415|| --- | --- | --- | 416|| -b, --by | auto | Grouping mode: auto, region, or site | 417|| -i, --impute | off | Treat missing genotypes as reference | 418|| -m, --max-diff | off | Merge haplotypes with difference ratio ≤ threshold [0,1] | 419| 420|Annotation options: 421| 422|| Option | Default | Description | 423|| --- | --- | --- | 424|| -g, --gff3, --gff | off | GFF3/GTF file for gene selectors and annotation | 425|| -u, --upstream | 0 | Upstream bases added to gene selectors | 426|| -d, --downstream | 0 | Downstream bases added to gene selectors | 427|| -a, --strand-aware | off | Apply upstream/downstream relative to gene strand | 428| 429|Sample/population options: 430| 431|| Option | Default | Description | 432|| --- | --- | --- | 433|| -S, --samples-file | off | Restrict to sample IDs in a file | 434|| -p, --population | off | Sample-to-population table (2 columns) | 435| 436|Output options: 437| 438|| Option | Default | Description | 439|| --- | --- | --- | 440|| -o, --output | summary | JSONL payload mode: summary or detail | 441|| -f, --output-format | tsv | Output format: tsv or jsonl | 442|| -O, --output-file | current directory | Output directory or prefix | 443| 444|Visualization options: 445| 446|| Option | Default | Description | 447|| --- | --- | --- | 448|| -P, --plot | off | Render haplotype table figure | 449|| -F, --plot-format | png | png, pdf, svg, or tiff | 450|| --table-theme | detailed | Table theme: detailed or compact | 451|| -z, --figsize | auto | Figure size as WIDTH,HEIGHT (inches) | 452|| -e, --geo | off | Sample coordinates for map plotting | 453|| --show-counts | off | Show sample-count labels at map pie centers | 454|| --hide-counts | off | Hide sample-count labels (default) | 455|| -n, --network | off | Render haplotype network | 456|| -N, --network-method | tcs | Network algorithm: tcs, msn, or mjn | 457| 458|Labeling options: 459| 460|| Option | Default | Description | 461|| --- | --- | --- | 462|| -H, --hap-prefix | Hap | Haplotype label prefix | 463|| -D, --hap-pad | 2 | Zero-padding width for labels | 464| 465|Notes: 466|- Exactly one selector is required: -r, -R, -t, -T, --gene-id, or --gene-list 467|- Targets supplied with -t or -T must all be on the same chromosome 468|- --gene-id and --gene-list require --gff/--gff3 469| 470|### haplokit phenotype 471| 472|text 473|haplokit phenotype -H <hapresult.tsv|sample_hap.tsv> -P <phenotype.tsv|phenotype.csv> [options] 474| 475| 476|Input options: 477| 478|| Option | Default | Description | 479|| --- | --- | --- | 480|| -H, --hapresult, --haplotypes | required | hapresult.tsv or two-column sample-haplotype table | 481|| -P, --phenotypes, --phenotype, --pheno-file | required | Phenotype table; first column is sample ID | 482|| -p, --population, --pop-group | off | Sample-to-population table | 483| 484|Test options: 485| 486|| Option | Default | Description | 487|| --- | --- | --- | 488|| -t, --trait | all numeric traits | Trait to analyze; repeatable for multiple traits | 489|| -m, --min-hap-size | 5 | Minimum numeric observations per test group | 490|| -M, --method | welch | Test method: welch, student, mannwhitney, or tukey | 491|| -a, --adjust | bonferroni | P-value adjustment: bonferroni or none (non-Tukey) | 492|| --remove-outliers | off | Remove Tukey IQR k=1.5 outliers before statistics | 493| 494|Output options: 495| 496|| Option | Default | Description | 497|| --- | --- | --- | 498|| -o, --output | phenotype_stats.tsv | Pairwise statistics TSV | 499|| -s, --summary-output | off | Per-haplotype summary TSV | 500| 501|