Introduction

Hapi is a novel easy-to-use and high-efficient algorithm that only requires 3 to 5 gametes to reconstruct accurate and high-resolution haplotypes of an individual. The gamete genotype data may be generated from various platforms including genotyping arrays and sequencing even with low-coverage. Hapi simply takes genotype data of known hetSNPs in single gamete cells as input and report the high-resolution haplotypes as well as the confidence level of each phased hetSNPs. The package also includes a module allowing downstream analyses and visualization of identified crossovers in the gametes.

Manual and R script

The comprehensive manual of Hapi is available here: Hapi Manual.
R code of the workflow is available here: Hapi Workflow

Installation

Installation from Github

Hapi can be easily installed from Github by running the following command in R:

### Install dependencies ahead
install.packages('devtools')
install.packages('HMM')
devtools::install_github('Jialab-UCR/Hapi')

If the installation fails with the ERROR: object 'enexprs' is not exported by 'namespace:rlang', please install the developmental version of rlang package first.

devtools::install_github("tidyverse/rlang", build_vignettes = TRUE)

Installation locally

On Windows system

• Download the package Hapi_0.0.1.tar.gz

• Make sure you have Rtools installed

• Add R and Rtools to the Path Variable on the Environment Variables panel, including

  c:\program files\Rtools\bin

  c:\program files\Rtools\gcc-4.6.3\bin

  c:\program files\R\R.3.x.x\bin\i386

  c:\program files\R\R.3.x.x\bin\x64

• Run the following command in R

### Install 'HMM' package ahead
install.packages('HMM')
install.packages('Hapi_0.0.1.tar.gz', repos = NULL, type='source')

On Linux and Mac systems

Directly run the following command in R

### Install 'HMM' package ahead
install.packages('HMM')
install.packages('Hapi_0.0.1.tar.gz', repos = NULL, type='source')