matt-shenton / HGRAINBOW

Supplementary data and scripts used in the article "Haplotype-based genome wide association study using a novel SNP-set method : RAINBOW"

HGRAINBOW

Supplementary data and scripts used in the article "Haplotype-based genome wide association study using a novel SNP-set method : RAINBOW"

Author : Kosuke Hamazaki ([e-mail])

Date : 2019/03/28

Here, I explain the structure of this repository.

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• HGRAINBOW
  • data.zip : This folder contains datasets analyzed in this study. Please download and then decompress.
    • extra : This folder contain datasets other than genotype and phenotype.
      • Table_S1_origin.csv : The original data for Table S1.
      • additive_relationship_matrix.RData : The additive genetic relationship matrix used in this study.
      • haplotype_block_list.csv : The list of haplotype block information used in the SNP-set GWAS methods.
      • map2.csv : The physical map corresponding to the haplotype block list.
    • genotype : The marker genotype used in this study.
      • L3024_core_extract_L414_ind1A_ind1B_MAF_0.025_geno.tsv : The marker genotype of 414 accessions used in this study.
      • L3024_core_extract_L414_ind1A_ind1B_MAF_0.025_haplo1.tsv : The marker haplotype of 414 accessions used in this study.
      • L3024_core_extract_L414_ind1A_ind1B_MAF_0.025_haplo2.tsv : The marker haplotype of 414 accessions used in this study.
    • phenotype : The phenotypic data simulated in this study.
      • number_of_causals=2_direction_of_effect=minus_trial_no=1.csv : The phenotypic data for the repulsion scenario.
      • number_of_causals=2_direction_of_effect=plus_trial_no=1.csv : The phenotypic data for the coupling scenario.
      • seeds_number_of_causals=2_direction_of_effect=minus_trial_no=1.csv : The random seeds used for simulating phenotypic data for the repulsion scenario.
      • seeds_number_of_causals=2_direction_of_effect=plus_trial_no=1.csv : The random seeds used for simulating phenotypic data for the coupling scenario.
  • scripts : This folder contains scripts with the R language used in this study.
    • 0.0_Rice_HGRAINBOW_subpop_list_to_generate_haplotype_data.R : Extract subpopulation list from 3,000 accessions.
    • 0.1_Rice_HGRAINBOW_haplotype_data.txt : Extract haplotype data of 414 accessions (plink and vcftools) adn estimate haplotype blocks by plink (not R!).
    • 0.2_Rice_HGRAINBOW_modyfing_haplotype_block_list.R : Modify haplotype block data estimated by plink into the format as data/extra/haplotype_block_list.csv.
    • 0.3_Rice_HGRAINBOW_Simulation_of_phenotypic_values_and_some_preparation.R : Simulate phenotypic values for both scenarios, coupling and repulsion.
    • 0.4_Rice_HGRAINBOW_subpop_list_for_Table_S1.R : Scripts for generating Table_S1_origin.csv.
    • 1.1_Rice_HGRAINBOW_score_SKAT_geneset.R : The function to run SKAT as haplotype-based GWAS method.
    • 1.2_Rice_HGRAINBOW_haplotype_group_fixed_GWAS.R : The function to run HGF as haplotype-based GWAS method.
    • 1.3_Rice_HGRAINBOW_SS_gwas.R : The function to calculate summary statistics from GWAS results.
    • 2.1_Rice_HGRAINBOW_Haplotype_based_GWAS_for_RAINBOW_package_paper.R : Perform each GWAS method and save the results.
    • 3.1_Rice_HGRAINBOW_Summary_of_HGRAINBOW_Haplotype_based_GWAS_for_RAINBOW.R : Summary GWAS results.
    • 3.2_Rice_HGRAINBOW_Manhattan_plot_from_the_results.R : Draw Manhattan plots from GWAS results.
    • 3.3_Rice_HGRAINBOW_Summary_plot_of_HGRAINBOW_Haplotype_based_GWAS_for_RAINBOW.R : Draw figures in the article from GWAS results.
    • 3.4_Rice_HGRAINBOW_Manhattan_plot_for_overwhelming_results.R : Draw Manhattan plots for overwhelming results (Figure 4).