Co-GWAS unveils the genetic architecture of inter-individual epistasis affecting biomass and disease severity in wheat binary mixtures

<p>The repository contains all the data and scripts required to perform the analysis and generate the figures and tables presented in the article: <br>"Co-GWAS unveils the genetic architecture of inter-individual epistasis affecting biomass and disease severity in wheat binary mixtures".</p> <p>0. DATA</p> <p>FOLDER: 0_Data<br>This folder contains the raw phenotypic and genotypic data.</p> <p>I. FILE PREPARATION</p> <p>FOLDER: 1_FilePrep_Design_Fig<br>The R script prepares the phenotypic and genotypic data for analysis and generates the kinship matrix. It also creates a figure illustrating the pairs of phenotyped genotypes.</p> <p>II. PHENOTYPIC ANALYSIS&nbsp;</p> <p>FOLDER: 2_GeneticEffects_PhenoCorr_Residus<br>The R script tests the significance of genetic effects, calculates the proportion of phenotypic variance explained for each phenotype, and checks for correlations between phenotypes. It also controls the residuals in the models.</p> <p>III. A. DGE-BASED GWAS</p> <p>FOLDER: 3_DGE_GWAS<br>This folder contains three subfolders for each phenotype (GWAS_DGE_B, GWAS_DGE_N, GWAS_DGE_P).<br>For example, the pycnidia folder contains the script 3.A_GWAS_DGE_P_AsREML_cluster.R, which performs DGE-based GWAS for the pycnidia phenotype.</p> <p>III. B. Analysis of GWAS Results for DGE</p> <p>FOLDER: 3_DGE_GWAS<br>Within the same folder, the script 3.B_Results_GWAS_DGE_P.Rmd combines the result files and produces Manhattan plots and plots of significant SNPs.</p> <p>IV. A. IGE-BASED GWAS</p> <p>FOLDER: 4_IGE_GWAS<br>This folder contains three subfolders for each phenotype (GWAS_IGE_B, GWAS_IGE_N, GWAS_IGE_P).<br>For example, the pycnidia folder contains the script 4.A_GWAS_IGE_P_AsREML_cluster.R, which performs IGE-based GWAS for the pycnidia phenotype.</p> <p>IV. B. Analysis of GWAS Results for IGE</p> <p>FOLDER: 4_IGE_GWAS<br>Within the same folder, the script 4.B_Results_GWAS_IGE_P.Rmd combines the result files and produces Manhattan plots and plots of significant SNPs.</p> <p>V. PREPARATION OF FILES FOR CO-GWAS</p> <p>FOLDER: 5_FilePrep_coGWAS<br>The script 5.A_FilePrep_coGWAS.Rmd prepares the phenotypic and genotypic data for analysis after SNP pruning.<br>The script 5.B_FilePrep_SNP_Pruning.R performs SNP pruning.<br>The script 5.C_Plot_SNP_Pruning_position.R plots the positions of SNPs before and after pruning.</p> <p>VI. CO-GWAS</p> <p>FOLDER: 6_coGWAS<br>This folder contains three subfolders for each phenotype (coGWAS_B, coGWAS_N, and coGWAS_P).&nbsp;<br>For example, the pycnidia folder contains the script 6.A_coGWAS_DGEIGE_P_Sommer_cluster.R, which performs the co-GWAS for the pycnidia phenotype.<br>The other scripts in this folder combine the result files.</p> <p>VII. HEATMAPS AND QQPLOT OF CO-GWAS RESULTS</p> <p>FOLDER: 7_Heatmaps_qqplots_coGWAS<br>This folder contains three subfolders for each phenotype (Heatmaps_qqplots_B, Heatmaps_qqplots_N, and Heatmaps_qqplots_P).<br>For example, the pycnidia subfolder includes two scripts: 7.A_coGWAS_P_Heatmaps.R generates heatmaps for the pycnidia phenotype and 7.B_coGWAS_P_qqplots.R produces the QQ plot.</p> <p>VIII. BOXPLOTS - 3D PLOTS - PHYSICAL MAPS</p> <p>FOLDER: 8_3Dplots_PhysicalMaps_Boxplots_coGWAS<br>This folder contains three subfolders for each phenotype (Boxplots_PhysicalMaps_3Dplots_B, Boxplots_PhysicalMaps_3Dplots_N, and Boxplots_PhysicalMaps_3Dplots_P).<br>For example, the pycnidia folder contains the script 8_coGWAS_P_Boxplots_PhysicalMaps_3Dplots.R, which generates 3D plots, boxplots and physical maps for the significant interactions.&nbsp;</p> <p>IX. CIRCULAR PLOTS &nbsp;</p> <p>FOLDER: 9_CircularPlots_coGWAS<br>This folder contains three subfolders for each phenotype (CircularPlots_B, CircularPlots_N, and CircularPlots_P).<br>For example, the pycnidia folder contains the script 9_coGWAS_P_CircularPlot.R, which generates the necessary files to create the circular plot.&nbsp;<br>The script circos.conf creates the circular plot.&nbsp;</p> <p>X. GO ENRICHMENT ANALYSIS&nbsp;</p> <p>FOLDER: 10_GOterms_coGWAS<br>This folder contains three subfolders for each phenotype (GOenrichments_B, GOenrichments_N, and GOenrichments_P).<br>For example, the pycnidia folder contains the script 10_coGWAS_P_GOenrichments.Rmd, which generates GO enrichment plots.</p>