Jwas: a Bayesian based GWAS and GS software developed by Julia

A little message

Now in the field of animal and plant genetic assessment , still Fortran Of the world , Believe in the future Julia It can take a place in the field of genome-wide selection .

Julia It's a magic language , It's said to be very fast , Also very friendly language . It starts with compiled languages C, C++ as well as Fortran We learn from speed , From dynamic language, for example R and Python Learn from the friendship . Julia It's the next generation of data science language . The future is very bright .

JWAS Is based on Julia To write , Can be in Jupyter netebook function , It's powerful , You can run single trait and multi trait mixed linear models , And support genomic data ( One step (single-step)) Analysis of .

The main function

Bayesian regression analysis

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• MCMC
• Bayes-alpha, Bayes-beta
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Basic analysis

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• Single linear mixed model
• Multiple character linear mixed model
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Genome data analysis

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• Genome wide prediction and selection (GS)
• Genome wide association analysis (GWAS)
  
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Julia Advantages in the field of genetic evaluation of animal and plant breeding

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• Julia Both speed and friendliness , A lot of software is based on compiled languages , such as C, C++ and Fortran, This makes them difficult to understand , Expansion and maintenance .
• Julia( And based on Julia Compiling JWAS), It's very easy to use multicore CPU perhaps GPU Programming
• JWAS Very good at speed
• Jupyter notebook Can be very friendly display code and results
• JWAS It's open source. , Researchers can be in Github Share and expand ideas and code .
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The project is hosted in Github On :

https://github.com/reworkhow/JWAS.jl

Document address :

http://reworkhow.github.io/JWAS.jl/latest/

reference

Cheng, H., Fernando, R. L., and Garrick, D. J. 2018 JWAS: Julia implementation of whole-genome analysis software. Proceedings of the World Congress on Genetics Applied to Livestock Production,11.859. Auckland, New Zealand.

Official account : Analysis of breeding data