GWAS of the Lövstad 2015 layer experiment.
-
R/prepare_marker_fasta.R -- Read SNP chip design file and output source sequences for alignment.
-
scripts/markers_run_blat.sh -- Use Blat to align sequences to Galgal6
-
R/markers_filter_alignment.R -- Read output from Blat and make a map file with new positions.
-
R/make_pheno_table.R -- Collect all phenotypes in one file
-
R/prepare_plink_files.R -- Reads text files of genotypes and phenotypes to create ped and phenotype files
-
R/plot_genotypes.R -- QC of SNP genotypes
-
R/plot_phenotypes.R -- Plots and linear models of bone strength and body weight
-
R/plot_pqct_tga_phenotypes.R -- Plots and linear models of pQCT and TGA phenotypes
-
R/trait_modelling_functions.R -- Helper functions
-
scripts/convert_bed.sh -- Convert binary plink files for GEMMA
-
script/gemma_grm.sh -- Estimate GRM with GEMMA
-
R/hglm_gwas_prepare_data.R -- Set up data for main bone and body weight GWAS
-
R/hglm_gwas_prepare_data_crosses_separate.R -- Separate crossbred analysis
-
R/hglm_gwas_summary_crosses_separate.R -- Main analysis of GWAS of bone and body weight with separate crossbreds
-
R/hglm_gwas_summary_pqct_crosses_separate.R -- Main analysis of GWAS of QCT phenotypes with separate crossbreds
-
R/hglm_gwas.R -- Old joint GWAS analysis of bone and body weight
-
R/hglm_gwas_tga_prepare_data.R -- Set up data for QCT and TGA GWAS
-
R/hglm_gwas_tga.R -- QCT and TGA GWAS
-
R/hglm_models.R -- Quantitative genetics models with hglm
-
R/hglm_models_tga.R -- Quantitative genetics models for QCT and TGA
-
R/R/hglm_gwas_overlap_crosses_separate.R -- Summarise main GWAS results
-
R/hglm_gwas_summary.R -- Old joint GWAS analysis
-
R/hglm_gwas_summary_pqct_tga.R -- Summarise QCT and TGA GWAS
-
R/hglm_gwas_overlap.R -- Overlap GWAS results between traits
-
R/candidate_loci.R -- Look at candidate loci
-
R/genomic_correlation_prepare_files.R -- Prepare data for genomic correlation with GCTA
-
scripts/genomic_correlation_gcta.sh -- Run bivariate genomic model with GCTA