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An algorithm for uncovering complementary sets of variants in GWAS

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Macarons

Macarons: a fast and simple algorithm to select complementary SNPs

Macarons is an algorithm designed to recover single nucleotide polymorphisms (SNPs) that are related with a phenotype in genome wide association studies (GWAS) by taking into account of the dependencies between them.

A developmental version of Macarons on Python is now available. For more information, please check out the related readme file.

Getting Started:

We provide a few examples on how to run Macarons on MATLAB. Simply run the demo file:

demo.m

In the provided examples, the genotype and flowering time phenotypes data of Arabidopsis Thaliana (AT) obtained from Atwell et. al. (2010) are used. For descriptions and format of the data, check the readme file for data.

Visualization of the selected variants

We also provide a demo that visualizes the correlation structure between the selected variants:

demo_visualization.m

Some examples:

License

This project is licensed under GNU GPL v3 - see the LICENSE file for details.

References

Yilmaz, S., Fakhouri, M., Koyuturk, M., Cicek, A. E. and Tastan, O. (2020). Uncovering complementary sets of variants for predicting quantitative phenotypes. bioRxiv

Atwell, S. et al. (2010) Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines. Nature, 465(7298), 627–631.

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