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MET_EC

Identifying key Environmental Covariates and quantifying their relationship associated with ear rot incidence in a multi-environment hybrid experiment

Sarah Lipps is the creator and manager of this repository (slipps@illinois.edu)

This manuscript is unpublished.

a_NASAPower_WeatherDownload

Downloading raw weather data for each environment using NasaPower (R) Environments with no planting or harvest date are skipped

b_GenerateECs_AllEnvs

Generating the many ECs I am interested in for the many environments

c_Format4SlidingWindow

Extensive formatting so that I can run the sliding-window pipeline Genotypes with no silking date are skipped.

d_Sliding Window

The sliding window function Windows are unique to each genotype in each environment.

e_WindowCorrelations

Correlations between ECs in each window. Windows are unique to each genotype in each environment. Correlation coefficients are bootstrapped

f_EWAS

Chi-squared test between models (1 with a single window-by-ec combination, and null model without)

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Identifying key Environmental Covariates and quantifying their relationship associated with ear rot incidence in a multi-environment hybrid experiment

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