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update mash_wrapper functions #395

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Merged
gaow merged 1 commit into from
May 28, 2025
Merged

update mash_wrapper functions #395

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29 changes: 14 additions & 15 deletions R/mash_wrapper.R
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Original file line number Diff line number Diff line change
Expand Up @@ -962,11 +962,12 @@ load_multicontext_sumstats <- function(dat_list, signal_df, cond, region, extrac
# Initialize output list
out <- list()
trait_names <- names(dat_list[[1]])
if (cond == "strong" && region %in% signal_df$gene_ID){
if (cond == "strong" && region %in% signal_df$gene_ID){
events <- signal_df %>% filter(gene_ID == region) %>% pull(event_ID) %>% unique()
for (j in 1:length(events)){
ref_df_filtered <- signal_df %>% filter(gene_ID == region, event_ID == events[j]) %>%
filter(!str_detect(context_classify, "NE"))
if(dim(ref_df_filtered)[1] == 0) next
## generate the reference panel for allele flipping
ref_panel <- parse_variant_id(ref_df_filtered$variant_ID%>%unique())

Expand All @@ -977,7 +978,7 @@ load_multicontext_sumstats <- function(dat_list, signal_df, cond, region, extrac

# Flatten the nested list
for (extract_inf in extract_infs) {
extracted_matrix <- merge_matrices(dat_list[[extract_inf]], value_column = extract_inf, ref_panel = ref_panel, id_column = "variants", remove_any_missing = FALSE)
extracted_matrix <- merge_sumstats_matrices(dat_list[[extract_inf]], value_column = extract_inf, ref_panel = ref_panel, id_column = "variants", remove_any_missing = FALSE)
out[[extract_inf]] <- extracted_matrix
# Set variant order on first iteration
if (is.null(var_idx)&& is.null(variants)) {
Expand Down Expand Up @@ -1013,21 +1014,20 @@ load_multicontext_sumstats <- function(dat_list, signal_df, cond, region, extrac
added_df <- data.frame()

# Ensure the column name of the numeric column

if (any(grepl("sQTL", df$context_classify))) {
if (any(grepl("sQTL", ref_df_filtered$context_classify))) {
if (any(grepl("sQTL|pQTL|gpQTL", df$context_classify))) {
if (any(grepl("sQTL|pQTL|gpQTL", ref_df_filtered$context_classify))) {

# Extract sQTL contexts to loop over
sQTL_specific_contexts <- unique(str_subset(ref_df_filtered$context_classify, "sQTL"))
xQTL_specific_contexts <- unique(str_subset(ref_df_filtered$context_classify, "sQTL|pQTL|gpQTL"))

for (context in sQTL_specific_contexts) {
for (cont in xQTL_specific_contexts) {
event_IDs_extracted <- ref_df_filtered %>%
filter(context_classify == context) %>%
filter(context_classify == cont) %>%
pull(event_IDs)

# Filter matching rows in df
context_rows <- df %>%
filter(context_classify == context, context %in% event_IDs_extracted)
filter(context_classify == cont, str_detect(context, paste(event_IDs_extracted, collapse = "|")))

if (nrow(context_rows) > 0) {
# Get the row with median absolute value
Expand All @@ -1037,14 +1037,13 @@ load_multicontext_sumstats <- function(dat_list, signal_df, cond, region, extrac
selected_df <- context_rows[median_idx, , drop = FALSE]

added_df <- bind_rows(added_df, selected_df)
df <- df %>% filter(context_classify != context)
df <- df %>% filter(context_classify !=cont)
}
}

# Combine updated sQTL-specific rows back into df
df <- bind_rows(df, added_df)
}
}
}
sumstats_df[[extract_inf]] <- df %>%
filter(!str_detect(context_classify, "NE") & context_classify != 'NA')%>%
group_by(context_classify) %>%
Expand Down Expand Up @@ -1083,7 +1082,7 @@ load_multicontext_sumstats <- function(dat_list, signal_df, cond, region, extrac
event_ID_extracted <- list()
for (extract_inf in extract_infs){
# Flatten the nested list
extracted_matrix <- merge_matrices(dat_list[[extract_inf]], value_column = extract_inf, ref_panel = ref_panel, id_column = "variants", remove_any_missing = FALSE)
extracted_matrix <- merge_sumstats_matrices(dat_list[[extract_inf]], value_column = extract_inf, ref_panel = ref_panel, id_column = "variants", remove_any_missing = FALSE)
out[[extract_inf]] <- extracted_matrix
# Set variant order on first iteration
if (is.null(var_idx)&& is.null(variants)) {
Expand Down Expand Up @@ -1122,7 +1121,7 @@ load_multicontext_sumstats <- function(dat_list, signal_df, cond, region, extrac
group_by(context_classify) %>%
filter(
!is.na(.data[[numeric_col]]),
if (any(str_detect(context_classify, "sQTL|pQTL"))) {
if (any(str_detect(context_classify, "sQTL|pQTL|gpQTL"))) {
abs(.data[[numeric_col]]) < 2
} else {
TRUE
Expand Down Expand Up @@ -1265,4 +1264,4 @@ extract_flatten_sumstats_from_nested <- function(data, extract_inf = "z", max_de

# Start search
return(find_nested(data))
}
}
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