https://github.com/senresearch/flxqtl.jl

A comprehensive QTL analysis tool by multivariate linear mixed model.
https://github.com/senresearch/flxqtl.jl

intel-hardware julia mkl qtl qtl-analysis

Last synced: about 1 month ago
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A comprehensive QTL analysis tool by multivariate linear mixed model.

• Host: GitHub
• URL: https://github.com/senresearch/flxqtl.jl
• Owner: senresearch
• License: gpl-3.0
• Created: 2020-11-13T22:58:00.000Z (about 4 years ago)
• Default Branch: master
• Last Pushed: 2024-10-07T23:14:06.000Z (3 months ago)
• Last Synced: 2024-10-18T21:03:50.846Z (2 months ago)
• Topics: intel-hardware, julia, mkl, qtl, qtl-analysis
• Language: Julia
• Homepage:
• Size: 1.91 MB
• Stars: 4
• Watchers: 2
• Forks: 7
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

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README

        
# FlxQTL

## *Fl*e*x*ible Multivariate Linear Mixed Model based *QTL* Analysis for Structured Multiple Traits

[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://senresearch.github.io/FlxQTL.jl/stable)

[![CI](https://github.com/senresearch/FlxQTL.jl/actions/workflows/ci.yml/badge.svg)](https://github.com/senresearch/FlxQTL.jl/actions/workflows/ci.yml)

[![codecov](https://codecov.io/gh/senresearch/FlxQTL.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/senresearch/FlxQTL.jl)

*FlxQTL.jl* is a package for a multivariate linear mixed model based

QTL analysis tool that supports incorporating information from trait

covariates such as time or different environments.  The package

supports computation of one-dimensional and two-dimensional

multivariate genome scans, visualization of genome scans, support for

LOCO (leave-one-chromosome-out), computation of kinship matrices, and

support for distributed computing.

![1D Genome Scan](images/ex1.png)

![2D Genome Scan](images/ex2.jpg)

The package is written in [Julia](https://www.julialang.org) and

includes extensive

[documentation](https://senresearch.github.io/FlxQTL.jl/stable).  If you

are new to Julia you may want to learn more by looking at [Julia

documentation](https://julialang.org).  Example data sets are located

in the [data](https://github.com/senresearch/FlxQTL.jl/tree/master/data)

directory.  For details about the method, you may want to read our

paper available as a

[preprint](https://doi.org/10.1101/2020.03.27.012690).

## Paper

Flexible multivariate linear mixed models for structured multiple

traits

Hyeonju Kim, Gregory Farage, John T. Lovell, John K. Mckay, Thomas

E. Juenger, Śaunak Sen

doi: https://doi.org/10.1101/2020.03.27.012690

## Installation

The package can installed in following ways.

In a Julia REPL, press `]` to enter a package mode,

```julia

julia> ]

pkg> add FlxQTL

```

Or, equivalently,

```julia

julia> using Pkg; Pkg.add("FlxQTL")

```

For installing from the source,

```julia

pkg> add https://github.com/senresearch/FlxQTL.jl

```

or,

```julia

julia> Pkg.add(url="https://github.com/senresearch/FlxQTL.jl")

```

To remove the package from the Julia REPL,

```julia

julia> ]

pkg> rm FlxQTL

```

Equivalently,

```julia

julia> using Pkg; Pkg.rm("FlxQTL")

```

## Choice of BLAS vendors

The package can be run with OpenBLAS (built-in Julia dense linear

algebra routines) or MKL (Intel's Math Kernel Library).  `MKL.jl`

works best on Intel hardware, but it can slightly improve performance

without Intel hardware.  For installation and details,

see: [MKL.jl](https://github.com/JuliaComputing/MKL.jl).