A Predictive Haplotyping Package

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 .

HaploCatcher

A Predictive Haplotyping Package

Introduction

This is a public repository for the R package 'HaploCatcher'. This package utilizes genome-wide molecular data, paired with historical locus/QTL/gene information, to train machine learning algorithms to produce predictive haplotype calls for lines which are genotyped with high density molecular platforms, yet not genotyped for the specific locus/QTL/gene in question. Any questions related to development, maintenance, and potential errors can be directed here.

Installation

To install HaploCatcher in R, users can use the following function taken from the devtools package:

# Install HaploCatcher
devtools::install_github("zjwinn/HaploCatcher")

It is recommended to install using the above code to get the most up-to-date version of HaploCatcher. To install from CRAN instead, use the following code in R:

# Install HaploCatcher from CRAN
install.packages("HaploCatcher")

Getting Started

To understand all necessary inputs for HaploCatcher, users can follow the tutorial laid out in the following R vignette titled, "An Intro to HaploCatcher." To call on the vignette directly from the R terminal, use the following R code after installing HaploCatcher:

# Call vignette
vignette("An_Intro_to_HaploCatcher")

News

See the release notes for a full history of changes. The current release, HaploCatcher 2.0.1, is a major restructure for speed and maintainability that also adds user-definable case labels (het_label / neg_label) so you are no longer locked into the gene / het_gene / non_gene naming convention.