R/finemap_loci.R
In RajLabMSSM/echolocatoR: Automated genomic fine-mapping
Defines functions
finemap_loci
Documented in
finemap_loci
#' Fine-map multiple loci
#'
#' \pkg{echolocatoR} will automatically fine-map each locus.
#' Uses the \code{topSNPs} data.frame to define locus coordinates.
#'
#' @family MAIN
#' @param loci The list of loci you want to fine-map.
#' If \code{subset_path="auto"} (\emph{default}),
#' a locus subset file name is automatically constructed as:
#' \emph{Data/<dataset_type>/<dataset_name>/<locus>/
#' Multi-finemap/<locus>_<dataset_name>_Multi-finemap.tsv.gz}
#' @param loci Character list of loci in \strong{Locus} col of \code{topSNPs}.
#' @param return_all Return a nested list of various the pipeline's outputs
#' including plots, tables, and file paths (default: \code{TRUE}).
#' If \code{FALSE}, instead only returns a single merged
#' \link[data.table]{data.table} containing the results from all loci.
#' @param use_tryCatch If an error is encountered in one locus,
#' the pipeline will continue to try running the rest of the loci
#' (default: \code{use_tryCatch=TRUE}). This avoid stopping all analyses due
#' to errors that only affect some loci,
#' but currently prevents debugging via traceback.
#' @inheritParams finemap_locus
#' @inheritParams echodata::standardize
#' @inheritParams echoconda::activate_env
#' @inheritParams echodata::filter_snps
#' @inheritParams echoLD::get_LD
#' @inheritParams echoLD::filter_LD
#' @inheritParams echoplot::plot_locus
#' @inheritParams echofinemap::multifinemap
#' @inheritParams echodata::find_consensus_snps
#'
#' @returns
#' By default, returns a nested list containing grouped by locus names
#' (e.g. \code{BST1}, \code{MEX3C}). The results of each locus contain
#' the following elements:
#' \itemize{
#' \item{\code{finemap_dat}}{ : Fine-mapping results from all selected methods
#' merged with the original summary statistics
#' (i.e. \strong{Multi-finemap results}). }
#' \item{\code{locus_plot}}{ : A nested list containing one or more
#' zoomed views of locus plots.}
#' \item{\code{LD_matrix}}{ : The post-processed LD matrix used
#' for fine-mapping.}
#' \item{\code{LD_plot}}{ : An LD plot (if used).}
#' \item{\code{locus_dir}}{ : Locus directory results are saved in.}
#' \item{\code{arguments}}{ : A record of the arguments supplied to
#' \link[echolocatoR]{finemap_loci}.}
#'}
#'In addition, the following object summarizes the results
#'from all the locus-specific results:
#' \itemize{
#' \item{\code{merged_dat}}{ : A merged \link[data.table]{data.table}
#' with all fine-mapping results from all loci.}
#'}
#'
#' @export
#' @importFrom echodata find_consensus_snps construct_colmap gene_locus_list
#' @importFrom data.table rbindlist data.table
#' @importFrom echofinemap POLYFUN_install
#'
#' @examples
#' topSNPs <- echodata::topSNPs_Nalls2019
#' fullSS_path <- echodata::example_fullSS(dataset = "Nalls2019")
#'
#' res <- echolocatoR::finemap_loci(
#' fullSS_path = fullSS_path,
#' topSNPs = topSNPs,
#' loci = c("BST1","MEX3C"),
#' finemap_methods = c("ABF","FINEMAP","SUSIE"),
#' dataset_name = "Nalls23andMe_2019",
#' fullSS_genome_build = "hg19",
#' bp_distance = 1000,
#' munged = TRUE)
finemap_loci <- function(#### Main args ####
loci = NULL,
fullSS_path,
fullSS_genome_build = NULL,
results_dir = file.path(tempdir(),"results"),
dataset_name = "dataset_name",
dataset_type = "GWAS",
topSNPs = "auto",
#### Force new args ####
force_new_subset = FALSE,
force_new_LD = FALSE,
force_new_finemap = FALSE,
#### Fine-mapping args ####
finemap_methods = c("ABF","FINEMAP","SUSIE"),
finemap_args = NULL,
n_causal = 5,
credset_thresh = .95,
consensus_thresh = 2,
fillNA = 0,
conditioned_snps = "auto",
priors_col = NULL,
#### Colname mapping args ####
munged = FALSE,
colmap = echodata::construct_colmap(munged = munged),
compute_n = "ldsc",
#### LD args ####
LD_reference = "1KGphase3",
LD_genome_build = "hg19",
leadSNP_LD_block = FALSE,
superpopulation = "EUR",
download_method = "axel",
#### SNP filter args ####
bp_distance = 500000,
min_POS = NA,
max_POS = NA,
min_MAF = NA,
trim_gene_limits = FALSE,
max_snps = NULL,
min_r2 = 0,
remove_variants = FALSE,
remove_correlates = FALSE,
#### Misc args ####
query_by = "tabix",
case_control = TRUE,
qtl_suffixes = NULL,
#### PLotting args ####
plot_types = c("simple"),
show_plot = TRUE,
zoom = "1x",
tx_biotypes = NULL,
nott_epigenome = FALSE,
nott_show_placseq = FALSE,
nott_binwidth = 200,
nott_bigwig_dir = NULL,
xgr_libnames = NULL,
roadmap = FALSE,
roadmap_query = NULL,
#### General args ####
remove_tmps = TRUE,
conda_env = "echoR_mini",
return_all = TRUE,
use_tryCatch = TRUE,
seed = 2022,
nThread = 1,
verbose = TRUE,
#### Deprecated args ####
top_SNPs = deprecated(),
PP_threshold = deprecated(),
consensus_threshold = deprecated(),
plot.Nott_epigenome = deprecated(),
plot.Nott_show_placseq = deprecated(),
plot.Nott_binwidth = deprecated(),
plot.Nott_bigwig_dir = deprecated(),
plot.Roadmap = deprecated(),
plot.Roadmap_query = deprecated(),
plot.XGR_libnames = deprecated(),
server = deprecated(),
plot.types = deprecated(),
plot.zoom = deprecated(),
QTL_prefixes = deprecated(),
vcf_folder = deprecated(),
probe_path = deprecated(),
file_sep=deprecated(),
## Deprecated colmap args
chrom_col=deprecated(),
chrom_type=deprecated(),
position_col=deprecated(),
snp_col=deprecated(),
pval_col=deprecated(),
effect_col=deprecated(),
stderr_col=deprecated(),
tstat_col=deprecated(),
locus_col=deprecated(),
freq_col=deprecated(),
MAF_col=deprecated(),
A1_col = deprecated(),
A2_col = deprecated(),
gene_col=deprecated(),
N_cases_col=deprecated(),
N_controls_col=deprecated(),
N_cases=deprecated(),
N_controls=deprecated(),
proportion_cases=deprecated(),
sample_size=deprecated(),
PAINTOR_QTL_datasets=deprecated()
){
# echoverseTemplate:::source_all();
# echoverseTemplate:::args2vars(finemap_loci);
#### Check for required args ####
force(fullSS_path)
### Check for deprecated args ####
check_deprecated(fun="finemap_loci",
args=match.call())
#### Check PolyFun/PAINTOR are installed early on (if needed) ####
if(any(grepl("polyfun",finemap_methods, ignore.case = TRUE))){
echofinemap::POLYFUN_install()
}
if(any(grepl("PAINTOR",finemap_methods, ignore.case = TRUE))){
echofinemap:::PAINTOR_install()
}
#### Parallise data.table functions ####
data.table::setDTthreads(threads = nThread);
#### Validate topSNPs ####
topSNPs <- check_topSNPs(topSNPs = topSNPs,
fullSS_path = fullSS_path,
verbose = verbose)
#### Get loci (if not supplied) ####
loci <- echodata::gene_locus_list(loci = loci,
topSNPs = topSNPs,
dataset_type = dataset_type,
verbose = verbose)
if(length(loci)==0){
stp <- '0 loci available to fine-map.'
stop(stp)
}
#### Validate fullSS genome build ####
fullSS_genome_build <- check_genome(fullSS_genome_build = fullSS_genome_build,
munged = colmap$munged,
fullSS_path = fullSS_path)
#### Select SNPs to condition on (for COJO) ####
conditioned_snps <- snps_to_condition(conditioned_snps = conditioned_snps,
topSNPs = topSNPs,
loci = loci)
#### Iterate fine-mapping over loci ####
t1 <- Sys.time()
FINEMAP_DAT <- lapply(seq_len(length(loci)),
function(i){
t1_locus <- Sys.time()
finemap_dat <- NULL
locus <- loci[i]
#### Locus header ####
cli::cat_boxx(
cli::col_br_cyan(
paste(cli::col_br_white(cli::style_blurred(")))>")),
bat_icon(), locus,
paste0("[locus ",i," / ",length(loci),"]"),
bat_icon(),
cli::col_br_white(cli::style_blurred("<((("))
)
)
)
tryCatch({
#### Check iterative arg lengths #####
n_causal_i <- arg_list_handler(arg = "n_causal",
i = i,
loci = loci)
trim_gene_limits_i <- arg_list_handler(arg = "trim_gene_limits",
i = i,
loci = loci)
conditioned_snps_i <- arg_list_handler(arg = "conditioned_snps",
i = i,
loci = loci,
use_names = TRUE,
error = FALSE)
bp_distance_i <- arg_list_handler(arg = "bp_distance",
i = i,
loci = loci)
min_POS_i <- arg_list_handler(arg = "min_POS",
i = i,
loci = loci)
max_POS_i <- arg_list_handler(arg = "max_POS",
i = i,
loci = loci)
LD_reference_i <- arg_list_handler(arg = "LD_reference",
i = i,
loci = loci)
LD_genome_build_i <- arg_list_handler(arg = "LD_genome_build",
i = i,
loci = loci)
#### Run pipeline ####
out_list <- finemap_locus(locus=locus,
topSNPs=topSNPs,
fullSS_path=fullSS_path,
fullSS_genome_build=fullSS_genome_build,
munged=munged,
colmap=colmap,
compute_n=compute_n,
priors_col=priors_col,
LD_genome_build=LD_genome_build_i,
results_dir=results_dir,
finemap_methods=finemap_methods,
finemap_args=finemap_args,
force_new_subset=force_new_subset,
force_new_LD=force_new_LD,
force_new_finemap=force_new_finemap,
dataset_name=dataset_name,
dataset_type=dataset_type,
n_causal=n_causal_i,
bp_distance=bp_distance_i,
LD_reference=LD_reference_i,
superpopulation=superpopulation,
download_method=download_method,
min_POS=min_POS_i,
max_POS=max_POS_i,
min_MAF=min_MAF,
trim_gene_limits=trim_gene_limits_i,
max_snps=max_snps,
min_r2=min_r2,
leadSNP_LD_block=leadSNP_LD_block,
query_by=query_by,
remove_variants=remove_variants,
remove_correlates=remove_correlates,
conditioned_snps=conditioned_snps_i,
remove_tmps=remove_tmps,
credset_thresh=credset_thresh,
consensus_thresh=consensus_thresh,
case_control=case_control,
qtl_suffixes=qtl_suffixes,
plot_types=plot_types,
show_plot=show_plot,
zoom=zoom,
tx_biotypes=tx_biotypes,
nott_epigenome=nott_epigenome,
nott_show_placseq=nott_show_placseq,
nott_binwidth=nott_binwidth,
nott_bigwig_dir=nott_bigwig_dir,
xgr_libnames=xgr_libnames,
roadmap=roadmap,
roadmap_query=roadmap_query,
seed=seed,
conda_env=conda_env,
nThread=nThread,
verbose=verbose)
#### Output list reminder ####
# list(finemap_dat
# locus_plot
# LD_matrix
# LD_plot
# locus_dir
# arguments)
messager("Formatting locus results.",v=verbose)
if(return_all) return(out_list)
finemap_dat <- out_list$finemap_dat
if(!"Locus" %in% colnames(finemap_dat)){
finemap_dat <- data.table::data.table(Locus=locus,
finemap_dat)
}
cat(' \n')
}, error = set_tryCatch(use_tryCatch = use_tryCatch)) ## end tryCatch()
report_time(t1 = t1_locus,
prefix = paste("Locus",locus,"complete in:"))
return(finemap_dat)
}) # end loop
#### Prepare results to return ####
steps("postprocess")
FINEMAP_DAT <- postprocess_data(FINEMAP_DAT=FINEMAP_DAT,
loci=loci,
credset_thresh=credset_thresh,
consensus_thresh=consensus_thresh,
return_all=return_all,
verbose=verbose)
report_time(t1 = t1,
prefix = "All loci done in:")
return(FINEMAP_DAT)
}
RajLabMSSM/echolocatoR documentation built on Jan. 29, 2023, 6:04 a.m.
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Defines functions finemap_loci
Documented in finemap_loci
#' Fine-map multiple loci
#'
#' \pkg{echolocatoR} will automatically fine-map each locus.
#' Uses the \code{topSNPs} data.frame to define locus coordinates.
#'
#' @family MAIN
#' @param loci The list of loci you want to fine-map.
#' If \code{subset_path="auto"} (\emph{default}),
#' a locus subset file name is automatically constructed as:
#' \emph{Data/<dataset_type>/<dataset_name>/<locus>/
#' Multi-finemap/<locus>_<dataset_name>_Multi-finemap.tsv.gz}
#' @param loci Character list of loci in \strong{Locus} col of \code{topSNPs}.
#' @param return_all Return a nested list of various the pipeline's outputs
#' including plots, tables, and file paths (default: \code{TRUE}).
#' If \code{FALSE}, instead only returns a single merged
#' \link[data.table]{data.table} containing the results from all loci.
#' @param use_tryCatch If an error is encountered in one locus,
#' the pipeline will continue to try running the rest of the loci
#' (default: \code{use_tryCatch=TRUE}). This avoid stopping all analyses due
#' to errors that only affect some loci,
#' but currently prevents debugging via traceback.
#' @inheritParams finemap_locus
#' @inheritParams echodata::standardize
#' @inheritParams echoconda::activate_env
#' @inheritParams echodata::filter_snps
#' @inheritParams echoLD::get_LD
#' @inheritParams echoLD::filter_LD
#' @inheritParams echoplot::plot_locus
#' @inheritParams echofinemap::multifinemap
#' @inheritParams echodata::find_consensus_snps
#'
#' @returns
#' By default, returns a nested list containing grouped by locus names
#' (e.g. \code{BST1}, \code{MEX3C}). The results of each locus contain
#' the following elements:
#' \itemize{
#' \item{\code{finemap_dat}}{ : Fine-mapping results from all selected methods
#' merged with the original summary statistics
#' (i.e. \strong{Multi-finemap results}). }
#' \item{\code{locus_plot}}{ : A nested list containing one or more
#' zoomed views of locus plots.}
#' \item{\code{LD_matrix}}{ : The post-processed LD matrix used
#' for fine-mapping.}
#' \item{\code{LD_plot}}{ : An LD plot (if used).}
#' \item{\code{locus_dir}}{ : Locus directory results are saved in.}
#' \item{\code{arguments}}{ : A record of the arguments supplied to
#' \link[echolocatoR]{finemap_loci}.}
#'}
#'In addition, the following object summarizes the results
#'from all the locus-specific results:
#' \itemize{
#' \item{\code{merged_dat}}{ : A merged \link[data.table]{data.table}
#' with all fine-mapping results from all loci.}
#'}
#'
#' @export
#' @importFrom echodata find_consensus_snps construct_colmap gene_locus_list
#' @importFrom data.table rbindlist data.table
#' @importFrom echofinemap POLYFUN_install
#'
#' @examples
#' topSNPs <- echodata::topSNPs_Nalls2019
#' fullSS_path <- echodata::example_fullSS(dataset = "Nalls2019")
#'
#' res <- echolocatoR::finemap_loci(
#' fullSS_path = fullSS_path,
#' topSNPs = topSNPs,
#' loci = c("BST1","MEX3C"),
#' finemap_methods = c("ABF","FINEMAP","SUSIE"),
#' dataset_name = "Nalls23andMe_2019",
#' fullSS_genome_build = "hg19",
#' bp_distance = 1000,
#' munged = TRUE)
finemap_loci <- function(#### Main args ####
loci = NULL,
fullSS_path,
fullSS_genome_build = NULL,
results_dir = file.path(tempdir(),"results"),
dataset_name = "dataset_name",
dataset_type = "GWAS",
topSNPs = "auto",
#### Force new args ####
force_new_subset = FALSE,
force_new_LD = FALSE,
force_new_finemap = FALSE,
#### Fine-mapping args ####
finemap_methods = c("ABF","FINEMAP","SUSIE"),
finemap_args = NULL,
n_causal = 5,
credset_thresh = .95,
consensus_thresh = 2,
fillNA = 0,
conditioned_snps = "auto",
priors_col = NULL,
#### Colname mapping args ####
munged = FALSE,
colmap = echodata::construct_colmap(munged = munged),
compute_n = "ldsc",
#### LD args ####
LD_reference = "1KGphase3",
LD_genome_build = "hg19",
leadSNP_LD_block = FALSE,
superpopulation = "EUR",
download_method = "axel",
#### SNP filter args ####
bp_distance = 500000,
min_POS = NA,
max_POS = NA,
min_MAF = NA,
trim_gene_limits = FALSE,
max_snps = NULL,
min_r2 = 0,
remove_variants = FALSE,
remove_correlates = FALSE,
#### Misc args ####
query_by = "tabix",
case_control = TRUE,
qtl_suffixes = NULL,
#### PLotting args ####
plot_types = c("simple"),
show_plot = TRUE,
zoom = "1x",
tx_biotypes = NULL,
nott_epigenome = FALSE,
nott_show_placseq = FALSE,
nott_binwidth = 200,
nott_bigwig_dir = NULL,
xgr_libnames = NULL,
roadmap = FALSE,
roadmap_query = NULL,
#### General args ####
remove_tmps = TRUE,
conda_env = "echoR_mini",
return_all = TRUE,
use_tryCatch = TRUE,
seed = 2022,
nThread = 1,
verbose = TRUE,
#### Deprecated args ####
top_SNPs = deprecated(),
PP_threshold = deprecated(),
consensus_threshold = deprecated(),
plot.Nott_epigenome = deprecated(),
plot.Nott_show_placseq = deprecated(),
plot.Nott_binwidth = deprecated(),
plot.Nott_bigwig_dir = deprecated(),
plot.Roadmap = deprecated(),
plot.Roadmap_query = deprecated(),
plot.XGR_libnames = deprecated(),
server = deprecated(),
plot.types = deprecated(),
plot.zoom = deprecated(),
QTL_prefixes = deprecated(),
vcf_folder = deprecated(),
probe_path = deprecated(),
file_sep=deprecated(),
## Deprecated colmap args
chrom_col=deprecated(),
chrom_type=deprecated(),
position_col=deprecated(),
snp_col=deprecated(),
pval_col=deprecated(),
effect_col=deprecated(),
stderr_col=deprecated(),
tstat_col=deprecated(),
locus_col=deprecated(),
freq_col=deprecated(),
MAF_col=deprecated(),
A1_col = deprecated(),
A2_col = deprecated(),
gene_col=deprecated(),
N_cases_col=deprecated(),
N_controls_col=deprecated(),
N_cases=deprecated(),
N_controls=deprecated(),
proportion_cases=deprecated(),
sample_size=deprecated(),
PAINTOR_QTL_datasets=deprecated()
){
# echoverseTemplate:::source_all();
# echoverseTemplate:::args2vars(finemap_loci);
#### Check for required args ####
force(fullSS_path)
### Check for deprecated args ####
check_deprecated(fun="finemap_loci",
args=match.call())
#### Check PolyFun/PAINTOR are installed early on (if needed) ####
if(any(grepl("polyfun",finemap_methods, ignore.case = TRUE))){
echofinemap::POLYFUN_install()
}
if(any(grepl("PAINTOR",finemap_methods, ignore.case = TRUE))){
echofinemap:::PAINTOR_install()
}
#### Parallise data.table functions ####
data.table::setDTthreads(threads = nThread);
#### Validate topSNPs ####
topSNPs <- check_topSNPs(topSNPs = topSNPs,
fullSS_path = fullSS_path,
verbose = verbose)
#### Get loci (if not supplied) ####
loci <- echodata::gene_locus_list(loci = loci,
topSNPs = topSNPs,
dataset_type = dataset_type,
verbose = verbose)
if(length(loci)==0){
stp <- '0 loci available to fine-map.'
stop(stp)
}
#### Validate fullSS genome build ####
fullSS_genome_build <- check_genome(fullSS_genome_build = fullSS_genome_build,
munged = colmap$munged,
fullSS_path = fullSS_path)
#### Select SNPs to condition on (for COJO) ####
conditioned_snps <- snps_to_condition(conditioned_snps = conditioned_snps,
topSNPs = topSNPs,
loci = loci)
#### Iterate fine-mapping over loci ####
t1 <- Sys.time()
FINEMAP_DAT <- lapply(seq_len(length(loci)),
function(i){
t1_locus <- Sys.time()
finemap_dat <- NULL
locus <- loci[i]
#### Locus header ####
cli::cat_boxx(
cli::col_br_cyan(
paste(cli::col_br_white(cli::style_blurred(")))>")),
bat_icon(), locus,
paste0("[locus ",i," / ",length(loci),"]"),
bat_icon(),
cli::col_br_white(cli::style_blurred("<((("))
)
)
)
tryCatch({
#### Check iterative arg lengths #####
n_causal_i <- arg_list_handler(arg = "n_causal",
i = i,
loci = loci)
trim_gene_limits_i <- arg_list_handler(arg = "trim_gene_limits",
i = i,
loci = loci)
conditioned_snps_i <- arg_list_handler(arg = "conditioned_snps",
i = i,
loci = loci,
use_names = TRUE,
error = FALSE)
bp_distance_i <- arg_list_handler(arg = "bp_distance",
i = i,
loci = loci)
min_POS_i <- arg_list_handler(arg = "min_POS",
i = i,
loci = loci)
max_POS_i <- arg_list_handler(arg = "max_POS",
i = i,
loci = loci)
LD_reference_i <- arg_list_handler(arg = "LD_reference",
i = i,
loci = loci)
LD_genome_build_i <- arg_list_handler(arg = "LD_genome_build",
i = i,
loci = loci)
#### Run pipeline ####
out_list <- finemap_locus(locus=locus,
topSNPs=topSNPs,
fullSS_path=fullSS_path,
fullSS_genome_build=fullSS_genome_build,
munged=munged,
colmap=colmap,
compute_n=compute_n,
priors_col=priors_col,
LD_genome_build=LD_genome_build_i,
results_dir=results_dir,
finemap_methods=finemap_methods,
finemap_args=finemap_args,
force_new_subset=force_new_subset,
force_new_LD=force_new_LD,
force_new_finemap=force_new_finemap,
dataset_name=dataset_name,
dataset_type=dataset_type,
n_causal=n_causal_i,
bp_distance=bp_distance_i,
LD_reference=LD_reference_i,
superpopulation=superpopulation,
download_method=download_method,
min_POS=min_POS_i,
max_POS=max_POS_i,
min_MAF=min_MAF,
trim_gene_limits=trim_gene_limits_i,
max_snps=max_snps,
min_r2=min_r2,
leadSNP_LD_block=leadSNP_LD_block,
query_by=query_by,
remove_variants=remove_variants,
remove_correlates=remove_correlates,
conditioned_snps=conditioned_snps_i,
remove_tmps=remove_tmps,
credset_thresh=credset_thresh,
consensus_thresh=consensus_thresh,
case_control=case_control,
qtl_suffixes=qtl_suffixes,
plot_types=plot_types,
show_plot=show_plot,
zoom=zoom,
tx_biotypes=tx_biotypes,
nott_epigenome=nott_epigenome,
nott_show_placseq=nott_show_placseq,
nott_binwidth=nott_binwidth,
nott_bigwig_dir=nott_bigwig_dir,
xgr_libnames=xgr_libnames,
roadmap=roadmap,
roadmap_query=roadmap_query,
seed=seed,
conda_env=conda_env,
nThread=nThread,
verbose=verbose)
#### Output list reminder ####
# list(finemap_dat
# locus_plot
# LD_matrix
# LD_plot
# locus_dir
# arguments)
messager("Formatting locus results.",v=verbose)
if(return_all) return(out_list)
finemap_dat <- out_list$finemap_dat
if(!"Locus" %in% colnames(finemap_dat)){
finemap_dat <- data.table::data.table(Locus=locus,
finemap_dat)
}
cat(' \n')
}, error = set_tryCatch(use_tryCatch = use_tryCatch)) ## end tryCatch()
report_time(t1 = t1_locus,
prefix = paste("Locus",locus,"complete in:"))
return(finemap_dat)
}) # end loop
#### Prepare results to return ####
steps("postprocess")
FINEMAP_DAT <- postprocess_data(FINEMAP_DAT=FINEMAP_DAT,
loci=loci,
credset_thresh=credset_thresh,
consensus_thresh=consensus_thresh,
return_all=return_all,
verbose=verbose)
report_time(t1 = t1,
prefix = "All loci done in:")
return(FINEMAP_DAT)
}
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