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xueweic merged 5 commits into from
Apr 18, 2025
Merged

pass unit test locally #57

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cdd0552
clean up model code
xueweic Apr 17, 2025
bed080a
Merge branch 'main' of https://github.com/xueweic/colocboost
xueweic Apr 17, 2025
79e8b40
monir fix bug
xueweic Apr 17, 2025
22783e2
pass unit test
xueweic Apr 18, 2025
69f16d7
Merge branch 'StatFunGen:main' into main
xueweic Apr 18, 2025
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62 changes: 22 additions & 40 deletions R/colocboost_check_update_jk.R
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Original file line number Diff line number Diff line change
Expand Up @@ -5,40 +5,22 @@
#'
#' @return update_status and real_update_jk for each trait
#' @noRd
colocboost_check_update_jk <- function(cb_model, cb_model_para, cb_data,
prioritize_jkstar = TRUE,
jk_equiv_corr = 0.8, ##### more than 2 traits
jk_equiv_loglik = 1, ## more than 2 traits
func_compare = "min_max", ##### more than 3 traits
coloc_thresh = 0.1) {
colocboost_check_update_jk <- function(cb_model, cb_model_para, cb_data) {

pos.update <- which(cb_model_para$update_y == 1)
focal_outcome_idx <- cb_model_para$focal_outcome_idx
if (is.null(focal_outcome_idx)) {
cb_model_para <- boost_check_update_jk_nofocal(cb_model, cb_model_para, cb_data,
prioritize_jkstar = prioritize_jkstar,
jk_equiv_corr = jk_equiv_corr,
jk_equiv_loglik = jk_equiv_loglik,
func_compare = func_compare,
coloc_thresh = coloc_thresh
)
cb_model_para <- boost_check_update_jk_nofocal(cb_model, cb_model_para, cb_data)
} else {
if (focal_outcome_idx %in% pos.update) {
cb_model_para <- boost_check_update_jk_focal(cb_model, cb_model_para, cb_data,
prioritize_jkstar = prioritize_jkstar,
jk_equiv_corr = jk_equiv_corr,
jk_equiv_loglik = jk_equiv_loglik,
func_compare = func_compare,
coloc_thresh = coloc_thresh,
cb_model_para <- boost_check_update_jk_focal(
cb_model,
cb_model_para,
cb_data,
focal_outcome_idx = focal_outcome_idx
)
} else {
cb_model_para <- boost_check_update_jk_nofocal(cb_model, cb_model_para, cb_data,
prioritize_jkstar = prioritize_jkstar,
jk_equiv_corr = jk_equiv_corr,
jk_equiv_loglik = jk_equiv_loglik,
func_compare = func_compare,
coloc_thresh = coloc_thresh
)
cb_model_para <- boost_check_update_jk_nofocal(cb_model, cb_model_para, cb_data)
}
}
return(cb_model_para)
Expand All @@ -47,12 +29,8 @@ colocboost_check_update_jk <- function(cb_model, cb_model_para, cb_data,


#' @importFrom stats median
boost_check_update_jk_nofocal <- function(cb_model, cb_model_para, cb_data,
prioritize_jkstar = TRUE,
jk_equiv_corr = 0.8, ##### more than 2 traits
jk_equiv_loglik = 1, ## more than 2 traits
func_compare = "min_max", ##### more than 3 traits
coloc_thresh = 0.1) {
boost_check_update_jk_nofocal <- function(cb_model, cb_model_para, cb_data) {

############# Output #################
# we will obtain and update the cb_model_para$update_status and cb_model_para$real_update_jk
######################################
Expand All @@ -61,9 +39,11 @@ boost_check_update_jk_nofocal <- function(cb_model, cb_model_para, cb_data,
update_status <- rep(0, cb_model_para$L)
update_jk <- rep(NA, cb_model_para$L + 1)
real_update_jk <- rep(NA, cb_model_para$L)
if (is.null(cb_model_para$coloc_thresh)) {
cb_model_para$coloc_thresh <- (1 - coloc_thresh) * max(sapply(1:length(cb_model), function(i) max(cb_model[[i]]$change_loglike)))
}
# - initial parameter
prioritize_jkstar <- cb_model_para$prioritize_jkstar
jk_equiv_corr <- cb_model_para$jk_equiv_corr
jk_equiv_loglik <- cb_model_para$jk_equiv_loglik
func_compare <- cb_model_para$func_compare

# - update only Ys which is not stop
pos.update <- which(cb_model_para$update_y == 1)
Expand Down Expand Up @@ -328,12 +308,8 @@ boost_check_update_jk_nofocal <- function(cb_model, cb_model_para, cb_data,


boost_check_update_jk_focal <- function(cb_model, cb_model_para, cb_data,
prioritize_jkstar = TRUE,
jk_equiv_corr = 0.8, ##### more than 2 traits
jk_equiv_loglik = 1, ## more than 2 traits
func_compare = "min_max", ##### more than 3 traits
coloc_thresh = 0.1,
focal_outcome_idx = 1) {

############# Output #################
# we will obtain and update the cb_model_para$update_status and cb_model_para$real_update_jk
######################################
Expand All @@ -345,6 +321,12 @@ boost_check_update_jk_focal <- function(cb_model, cb_model_para, cb_data,
if (is.null(cb_model_para$coloc_thresh)) {
cb_model_para$coloc_thresh <- (1 - coloc_thresh) * max(sapply(1:length(cb_model), function(i) max(cb_model[[i]]$change_loglike)))
}
# - initial parameter
prioritize_jkstar <- cb_model_para$prioritize_jkstar
jk_equiv_corr <- cb_model_para$jk_equiv_corr
jk_equiv_loglik <- cb_model_para$jk_equiv_loglik
func_compare <- cb_model_para$func_compare
coloc_thresh <- cb_model_para$coloc_thresh

# - update only Ys which is not stop
pos.update <- which(cb_model_para$update_y == 1)
Expand Down
24 changes: 20 additions & 4 deletions R/colocboost_init.R
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Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,7 @@ colocboost_inits <- function() {
colocboost_init_data <- function(X, Y, dict_YX,
Z, LD, N_sumstat, dict_sumstatLD,
Var_y, SeBhat,
keep_variables = NULL,
keep_variables,
focal_outcome_idx = NULL,
focal_outcome_variables = TRUE,
overlap_variables = FALSE,
Expand Down Expand Up @@ -213,12 +213,20 @@ colocboost_init_model <- function(cb_data,
#' @importFrom utils tail
colocboost_init_para <- function(cb_data, cb_model, tau = 0.01,
func_simplex = "z2z",
lambda = 0.5, lambda_focal_outcome = 1,
lambda = 0.5,
lambda_focal_outcome = 1,
learning_rate_decay = 1,
multi_test_thresh = 1,
func_multi_test = "lfdr",
LD_free = FALSE,
outcome_names = NULL,
focal_outcome_idx = NULL) {
focal_outcome_idx = NULL,
dynamic_learning_rate = TRUE,
prioritize_jkstar = TRUE,
jk_equiv_corr = 0.8,
jk_equiv_loglik = 1,
func_compare = "min_max",
coloc_thresh = 0.1) {
################# initialization #######################################
# - sample size
N <- sapply(cb_data$data, function(dt) dt$N)
Expand Down Expand Up @@ -251,7 +259,8 @@ colocboost_init_para <- function(cb_data, cb_model, tau = 0.01,
} else {
outcome_names <- paste0("Y", 1:L)
}

# - initial coloc_thresh
coloc_thresh <- (1 - coloc_thresh) * max(sapply(1:length(cb_model), function(i) max(cb_model[[i]]$change_loglike)))
cb_model_para <- list(
"L" = L,
"P" = P,
Expand All @@ -260,7 +269,14 @@ colocboost_init_para <- function(cb_data, cb_model, tau = 0.01,
"func_simplex" = func_simplex,
"lambda" = lambda,
"lambda_focal_outcome" = lambda_focal_outcome,
"learning_rate_decay" = learning_rate_decay,
"profile_loglike" = profile_loglike,
"dynamic_learning_rate" = dynamic_learning_rate,
"prioritize_jkstar" = prioritize_jkstar,
"jk_equiv_corr" = jk_equiv_corr,
"jk_equiv_loglik" = jk_equiv_loglik,
"func_compare" = func_compare,
"coloc_thresh" = coloc_thresh,
"update_status" = c(),
"jk" = c(),
"update_y" = update_y,
Expand Down
115 changes: 36 additions & 79 deletions R/colocboost_one_causal.R
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Original file line number Diff line number Diff line change
Expand Up @@ -13,37 +13,13 @@
#' @rdname colocboost_one_causal
#' @keywords cb_one_causal
#' @noRd
colocboost_one_causal <- function(cb_model, cb_model_para, cb_data,
jk_equiv_corr = 0.8,
jk_equiv_loglik = 1,
tau = 0.01,
learning_rate_decay = 1,
func_simplex = "z2z",
lambda = 0.5,
lambda_focal_outcome = 1,
LD_free = FALSE) {
if (jk_equiv_corr != 0) {
cb_obj <- colocboost_one_iteration(cb_model, cb_model_para, cb_data,
jk_equiv_corr = jk_equiv_corr,
jk_equiv_loglik = jk_equiv_loglik,
tau = tau,
learning_rate_decay = learning_rate_decay,
func_simplex = func_simplex,
lambda = lambda,
lambda_focal_outcome = lambda_focal_outcome,
LD_free = LD_free
)
colocboost_one_causal <- function(cb_model, cb_model_para, cb_data) {

if (cb_model_para$jk_equiv_corr != 0) {
cb_obj <- colocboost_one_iteration(cb_model, cb_model_para, cb_data)

} else {
cb_obj <- colocboost_diagLD(cb_model, cb_model_para, cb_data,
jk_equiv_corr = jk_equiv_corr,
jk_equiv_loglik = jk_equiv_loglik,
tau = tau,
learning_rate_decay = learning_rate_decay,
func_simplex = func_simplex,
lambda = lambda,
lambda_focal_outcome = lambda_focal_outcome,
LD_free = LD_free
)
cb_obj <- colocboost_diagLD(cb_model, cb_model_para, cb_data)
}
return(cb_obj)
}
Expand All @@ -64,21 +40,15 @@ colocboost_one_causal <- function(cb_model, cb_model_para, cb_data,
#'
#' @keywords cb_one_causal
#' @noRd
colocboost_one_iteration <- function(cb_model, cb_model_para, cb_data,
jk_equiv_corr = 0.8,
jk_equiv_loglik = 1,
tau = 0.01,
learning_rate_decay = 1,
func_simplex = "z2z",
lambda = 0.5,
lambda_focal_outcome = 1,
LD_free = FALSE) {
colocboost_one_iteration <- function(cb_model, cb_model_para, cb_data) {

if (sum(cb_model_para$update_y == 1) != 0) {
######## - some traits updated
# - step 1: check update clusters
real_update <- boost_check_update_jk_one_causal(cb_model, cb_model_para, cb_data,
jk_equiv_corr = jk_equiv_corr,
jk_equiv_loglik = jk_equiv_loglik
real_update <- boost_check_update_jk_one_causal(
cb_model,
cb_model_para,
cb_data
)

# - step 2: boost update
Expand All @@ -89,13 +59,10 @@ colocboost_one_iteration <- function(cb_model, cb_model_para, cb_data,
cb_model_para$update_status <- cbind(cb_model_para$update_status, as.matrix(real_update[[i_update]]$update_status))
cb_model_para$real_update_jk <- rbind(cb_model_para$real_update_jk, real_update[[i_update]]$real_update_jk)
# - update cb_model
cb_model <- colocboost_update(cb_model, cb_model_para, cb_data,
tau = tau,
learning_rate_decay = learning_rate_decay,
func_simplex = func_simplex,
lambda = lambda,
lambda_focal_outcome = lambda_focal_outcome,
LD_free = LD_free
cb_model <- colocboost_update(
cb_model,
cb_model_para,
cb_data
)
}
}
Expand Down Expand Up @@ -130,10 +97,8 @@ colocboost_one_iteration <- function(cb_model, cb_model_para, cb_data,
#'
#' @keywords cb_one_causal
#' @noRd
boost_check_update_jk_one_causal <- function(cb_model, cb_model_para, cb_data,
prioritize_jkstar = TRUE,
jk_equiv_corr = 0.8,
jk_equiv_loglik = 1) {
boost_check_update_jk_one_causal <- function(cb_model, cb_model_para, cb_data) {

pos.update <- which(cb_model_para$update_y == 1)
update_jk <- rep(NA, cb_model_para$L + 1)
# - check pairwise equivalent of jk
Expand Down Expand Up @@ -169,8 +134,8 @@ boost_check_update_jk_one_causal <- function(cb_model, cb_model_para, cb_data,
model_update = model_update,
cb_data = cb_data,
X_dict = X_dict,
jk_equiv_corr = jk_equiv_corr,
jk_equiv_loglik = jk_equiv_loglik
jk_equiv_corr = cb_model_para$jk_equiv_corr,
jk_equiv_loglik = cb_model_para$jk_equiv_loglik
)
# define category with same jk
temp <- sapply(1:nrow(change_each_pair), function(x) {
Expand Down Expand Up @@ -214,15 +179,8 @@ boost_check_update_jk_one_causal <- function(cb_model, cb_model_para, cb_data,
#'
#' @keywords cb_one_causal
#' @noRd
colocboost_diagLD <- function(cb_model, cb_model_para, cb_data,
jk_equiv_corr = 0,
jk_equiv_loglik = 0.1,
tau = 0.01,
learning_rate_decay = 1,
func_simplex = "z2z",
lambda = 0.5,
lambda_focal_outcome = 1,
LD_free = FALSE) {
colocboost_diagLD <- function(cb_model, cb_model_para, cb_data) {

if (sum(cb_model_para$update_y == 1) == 1) {
pos.update <- which(cb_model_para$update_y == 1)
update_jk <- rep(NA, cb_model_para$L + 1)
Expand All @@ -242,9 +200,10 @@ colocboost_diagLD <- function(cb_model, cb_model_para, cb_data,
cb_model_para$jk <- rbind(cb_model_para$jk, update_jk)
cb_model_para$update_status <- cbind(cb_model_para$update_status, as.matrix(update_status))
cb_model_para$real_update_jk <- rbind(cb_model_para$real_update_jk, real_update_jk)
cb_model <- colocboost_update(cb_model, cb_model_para, cb_data,
tau = tau, learning_rate_decay = learning_rate_decay, func_simplex = func_simplex,
lambda = lambda, lambda_focal_outcome = lambda_focal_outcome, LD_free = LD_free
cb_model <- colocboost_update(
cb_model,
cb_model_para,
cb_data
)
}

Expand Down Expand Up @@ -273,9 +232,10 @@ colocboost_diagLD <- function(cb_model, cb_model_para, cb_data,
"real_update_jk" = real_update_jk
)
# - update cb_model
cb_model_tmp <- colocboost_update(cb_model_tmp, cb_model_para, cb_data,
tau = tau, learning_rate_decay = learning_rate_decay, func_simplex = func_simplex,
lambda = lambda, lambda_focal_outcome = lambda_focal_outcome, LD_free = LD_free
cb_model_tmp <- colocboost_update(
cb_model_tmp,
cb_model_para,
cb_data
)
weights <- rbind(weights, cb_model_tmp[[iy]]$weights_path)
}
Expand All @@ -286,8 +246,8 @@ colocboost_diagLD <- function(cb_model, cb_model_para, cb_data,
model_update = model_update,
cb_data = cb_data,
X_dict = X_dict,
jk_equiv_corr = jk_equiv_corr,
jk_equiv_loglik = jk_equiv_loglik
jk_equiv_corr = cb_model_para$jk_equiv_corr,
jk_equiv_loglik = cb_model_para$jk_equiv_loglik
)
change_each_pair <- change_each_pair * overlap_pair
# define category with same jk
Expand Down Expand Up @@ -327,13 +287,10 @@ colocboost_diagLD <- function(cb_model, cb_model_para, cb_data,
cb_model_para$update_status <- cbind(cb_model_para$update_status, as.matrix(real_update[[i_update]]$update_status))
cb_model_para$real_update_jk <- rbind(cb_model_para$real_update_jk, real_update[[i_update]]$real_update_jk)
# - update cb_model
cb_model <- colocboost_update(cb_model, cb_model_para, cb_data,
tau = tau,
learning_rate_decay = learning_rate_decay,
func_simplex = func_simplex,
lambda = lambda,
lambda_focal_outcome = lambda_focal_outcome,
LD_free = LD_free
cb_model <- colocboost_update(
cb_model,
cb_model_para,
cb_data
)
}
}
Expand Down
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