Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#",
root.dir = getwd()
)
## ----load data, eval = FALSE--------------------------------------------------
# library(simplePHENOTYPES)
# data("SNP55K_maize282_maf04")
# SNP55K_maize282_maf04[1:8, 1:10]
## ----ST, eval = FALSE---------------------------------------------------------
# create_phenotypes(
# geno_obj = SNP55K_maize282_maf04,
# add_QTN_num = 3,
# add_effect = 0.2,
# big_add_QTN_effect = 0.9,
# rep = 10,
# h2 = 0.7,
# model = "A",
# home_dir = tempdir())
## ----MT P, results = "hide", eval = FALSE-------------------------------------
# test1 <- create_phenotypes(
# geno_obj = SNP55K_maize282_maf04,
# add_QTN_num = 3,
# dom_QTN_num = 4,
# big_add_QTN_effect = c(0.3, 0.3, 0.3),
# h2 = c(0.2, 0.4, 0.4),
# add_effect = c(0.04,0.2,0.1),
# dom_effect = c(0.04,0.2,0.1),
# ntraits = 3,
# rep = 10,
# vary_QTN = FALSE,
# output_format = "multi-file",
# architecture = "pleiotropic",
# output_dir = "Results_Pleiotropic",
# to_r = TRUE,
# seed = 10,
# model = "AD",
# sim_method = "geometric",
# home_dir = tempdir()
# )
## ----MT P2, results = "hide", eval = FALSE------------------------------------
# custom_geometric_a <- list(trait_1 = c(0.04, 0.0016),
# trait_2 = c(0.2, 0.04),
# trait_3 = c(0.1, 0.01))
# custom_geometric_d <- list(trait_1 = c(0.04, 0.0016, 6.4e-05, 2.56e-06),
# trait_2 = c(0.2, 0.04, 0.008, 0.0016),
# trait_3 = c(0.1, 0.01, 0.001, 1e-04))
#
# test2 <- create_phenotypes(
# geno_obj = SNP55K_maize282_maf04,
# add_QTN_num = 3,
# dom_QTN_num = 4,
# big_add_QTN_effect = c(0.3, 0.3, 0.3),
# h2 = c(0.2,0.4, 0.4),
# add_effect = custom_geometric_a,
# dom_effect = custom_geometric_d,
# ntraits = 3,
# rep = 10,
# vary_QTN = FALSE,
# output_format = "multi-file",
# architecture = "pleiotropic",
# output_dir = "Results_Pleiotropic",
# to_r = T,
# sim_method = "custom",
# seed = 10,
# model = "AD",
# home_dir = tempdir()
# )
#
# all.equal(test1, test2)
## ----MT PP, results = "hide", eval = FALSE------------------------------------
# cor_matrix <- matrix(c( 1, 0.3, -0.9,
# 0.3, 1, -0.5,
# -0.9, -0.5, 1 ), 3)
#
# sim_results <- create_phenotypes(
# geno_obj = SNP55K_maize282_maf04,
# ntraits = 3,
# pleio_a = 3,
# pleio_e = 2,
# same_add_dom_QTN = TRUE,
# degree_of_dom = 0.5,
# trait_spec_a_QTN_num = c(4, 10, 1),
# trait_spec_e_QTN_num = c(3, 2, 5),
# h2 = c(0.2, 0.4, 0.8),
# add_effect = c(0.5, 0.33, 0.2),
# epi_effect = c(0.3, 0.3, 0.3),
# epi_interaction = 2,
# cor = cor_matrix,
# rep = 20,
# output_dir = "Results_Partially",
# output_format = "long",
# architecture = "partially",
# out_geno = "numeric",
# to_r = TRUE,
# model = "AE",
# home_dir = tempdir()
# )
## ----MT LD, results = "hide", eval = FALSE------------------------------------
# create_phenotypes(
# geno_obj = SNP55K_maize282_maf04,
# add_QTN_num = 3,
# h2 = c(0.2, 0.4),
# add_effect = c(0.02, 0.05),
# rep = 5,
# seed = 200,
# output_format = "wide",
# architecture = "LD",
# output_dir = "Results_LD",
# out_geno = "BED",
# remove_QTN = TRUE,
# ld_max =0.8,
# ld_min =0.2,
# model = "A",
# ld_method = "composite",
# type_of_ld = "indirect",
# home_dir = tempdir()
# )
## ----MT PP E, results = "hide", eval = FALSE----------------------------------
# residual <- matrix(c(1, 0.1,-0.2,
# 0.1, 1,-0.1,-0.2,-0.1, 1), 3)
# heritability <- matrix(c(0.2, 0.4, 0.8,
# 0.6, 0.7, 0.2), 2)
# create_phenotypes(
# geno_obj = SNP55K_maize282_maf04,
# pleio_a = 3,
# pleio_e = 2,
# same_add_dom_QTN = TRUE,
# degree_of_dom = 1,
# trait_spec_a_QTN_num = c(4, 10, 1),
# trait_spec_e_QTN_num = c(2, 1, 5),
# epi_effect = c(0.01, 0.4, 0.2),
# add_effect = c(0.3, 0.2, 0.5),
# h2 = heritability,
# ntraits = 3,
# rep = 5,
# vary_QTN = TRUE,
# warning_file_saver = FALSE,
# output_dir = "Results_Partially_ADE",
# output_format = "gemma",
# architecture = "partially",
# model = "ADE",
# QTN_variance = TRUE,
# remove_QTN = TRUE,
# home_dir = tempdir(),
# constraints = list(
# maf_above = 0.3,
# maf_below = 0.44,
# hets = "include"
# ),
# cor_res = residual
# )
## ----qtn_list, results = "hide", eval = FALSE---------------------------------
# QTN_list <- list()
# QTN_list$add[[1]] <- c("ss196523212")
# QTN_list$dom[[1]] <- c("ss196510214", "ss196472187")
# QTN_list$epi[[1]] <- c("ss196530605", "ss196475446")
# create_phenotypes(
# geno_obj = SNP55K_maize282_maf04,
# add_QTN_num = 1,
# dom_QTN_num = 2,
# epi_QTN_num = 1,
# epi_interaction = 2,
# h2 = c(0.92, 0.4) ,
# add_effect = c(0.90, 0.2),
# dom_effect = c(0.01, 0.3),
# epi_effect = c(-0.3, 0.7),
# ntraits = 2,
# QTN_list = QTN_list,
# rep = 1,
# output_format = "gemma",
# out_geno = "BED",
# output_dir = "output_data",
# model = "ADE",
# home_dir = getwd()
# )
#
## ----example, results = "hide", eval = FALSE----------------------------------
# create_phenotypes(
# geno_path = "PATH/TO/FILE",
# prefix = "WGS_chrm_",
# add_QTN_num = 3,
# h2 = 0.2,
# add_effect = 0.02,
# rep = 5,
# seed = 200,
# output_format = "gemma",
# output_dir = "Results",
# model = "ADE",
# home_dir = tempdir()
# )
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