A Predictive Haplotyping Package
Overview
Used for predicting a genotype's allelic state at a specific locus/QTL/gene. This is accomplished by using both a genotype matrix and a separate file which has categorizations about loci/QTL/genes of interest for the individuals in the genotypic matrix. A training population can be created from a panel of individuals who have been previously screened for specific loci/QTL/genes, and this previous screening could be summarized into a category. Using the categorization of individuals which have been genotyped using a genome wide marker platform, a model can be trained to predict what category (haplotype) an individual belongs in based on their genetic sequence in the region associated with the locus/QTL/gene. These trained models can then be used to predict the haplotype of a locus/QTL/gene for individuals which have been genotyped with a genome wide platform yet not genotyped for the specific locus/QTL/gene. This package is based off work done by Winn et al 2021. For more specific information on this method, refer to doi:10.1007/s00122-022-04178-w.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK13 OK2026-05-02
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- ERROR11 OK, 1 ERROR2026-04-25
- OK14 OK2026-03-10
Documentation
- Help pages
- 10 (1 internal)includes a package overview page
- Examples that run
- 100%9 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
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- Help pages citing references
- 0%
Downloads
Repository
- PRs merged (all time)
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- Median days to close, 50 most recently updated closed issues
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- Median days to close, 50 most recently updated closed PRs
- 81
4 development-tooling and community-health practices detected across 2 families in the upstream repository
Checks run against github.com/zjwinn/haplocatcher on 2026-10-21.
Dependencies
Installing HaploCatcher adds 71 packages (37 with compiled code, 53 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.
Code & Tests
Datasets
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- 2.0.1Latest
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 1.0.42023-04-22 · diff ↗
- RR 4.3.0 released · 2023-04-21
- 1.0.32023-04-04
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2023-04-04
- Total releases
- 3 / 3 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 283 KB / 3 files
- Download size
- 741 KB
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