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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.
The comprehensive manual of Hapi
is available here: Hapi
Manual.
R code of the workflow is available here: Hapi
Workflow
Hapi
can be easily installed from Github by running the
following command in R:
### Install dependencies ahead
install.packages('devtools')
install.packages('HMM')
::install_github('Jialab-UCR/Hapi') devtools
If the installation fails with the ERROR: object ‘enexprs’ is not
exported by ‘namespace:rlang’, please install the developmental version
of rlang
package first.
::install_github("tidyverse/rlang", build_vignettes = TRUE) devtools
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:files
c:files.3
c:files.3.x.x386
c:files.3.x.x
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')
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')
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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