## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse  = TRUE,
  comment   = "#>",
  eval      = FALSE
)

## ----install-cran-------------------------------------------------------------
# install.packages("easyLSEA")

## ----install-github-----------------------------------------------------------
# # install.packages("remotes")
# remotes::install_github("DavidGO464/easyLSEA")

## ----install-fgsea------------------------------------------------------------
# BiocManager::install("fgsea")

## ----quickstart---------------------------------------------------------------
# library(easyLSEA)
# 
# result <- easyLSEA(
#   data      = my_lipid_data,
#   lipid_col = "LipidName",
#   fc_col    = "logFC",
#   pval_col  = "P.Value",
#   case_lbl  = "NASH",
#   ref_lbl   = "Control",
#   engine    = "both",   # run KS and fgsea
#   min_rank  = "E"       # include all confidence ranks except P and NA (default)
# )

## ----meta---------------------------------------------------------------------
# result$meta$date
# result$meta$case_lbl
# result$meta$n_lipids

## ----lsea---------------------------------------------------------------------
# # KS results — one row per lipid set per grouping level
# head(result$lsea$ks)
# 
# # fgsea results
# head(result$lsea$fgsea)
# 
# # Combined table with Convergence column
# head(result$lsea$combined)

## ----chains-------------------------------------------------------------------
# # Long format — one row per acyl chain per lipid
# head(result$chains$parsed)
# 
# # Parsing status — one row per lipid
# head(result$chains$summary)
# 
# # Wide format — one row per lipid with sn positions and totals
# head(result$chains$wide)

## ----plots-list---------------------------------------------------------------
# # List all available plots
# names(result$plots$lsea)
# names(result$plots$chains)

## ----input--------------------------------------------------------------------
# # Annotated data with LipidClass, LipidCategory_LMAPS, etc.
# head(result$input$data)
# 
# # Grouping columns tested
# result$input$group_cols

## ----view-plots---------------------------------------------------------------
# # KS bubble plot — all lipid classes
# result$plots$lsea$bubble_ks_01_Class
# 
# # fgsea bubble plot — significant sets only
# result$plots$lsea$bubble_fgsea_sig_01_Class
# 
# # Distribution plot — lipid class level
# result$plots$lsea$dist_01_Class

## ----bubble-label-------------------------------------------------------------
# # Regenerate plots showing only FDR and n
# plots <- plot_lsea(
#   result$lsea,
#   case_lbl     = "NASH",
#   ref_lbl      = "Control",
#   bubble_label = c("FDR", "n")
# )

## ----export-------------------------------------------------------------------
# export_lsea(
#   result,
#   dir    = tempdir(),
#   format = c("csv", "excel", "pdf")
# )

## ----advanced-separate--------------------------------------------------------
# # Step 1: annotate
# annotated <- annotate_lipids(my_lipid_data, lipid_col = "LipidName")
# 
# # Step 2: run enrichment
# lsea_res <- run_lsea(
#   data      = annotated,
#   fc_col    = "logFC",
#   engine    = "both",
#   case_lbl  = "NASH",
#   ref_lbl   = "Control"
# )
# 
# # Step 3: generate plots manually
# plots <- plot_lsea(
#   lsea_res,
#   case_lbl     = "NASH",
#   ref_lbl      = "Control",
#   fdr_thresh   = 0.05,
#   bubble_label = c("FDR", "DS", "NES", "n")
# )
# 
# # Step 4: distribution plot for a specific level
# p_dist <- plot_distribution(
#   data        = annotated,
#   lsea_result = lsea_res,
#   group_col   = "LipidClass",
#   case_lbl    = "NASH",
#   ref_lbl     = "Control"
# )

## ----fgsea-rank---------------------------------------------------------------
# # Default: pi-value = sign(logFC) * -log10(P.Value)
# # Combines effect size and statistical evidence
# 
# # Alternative: logFC only
# result_fc <- easyLSEA(
#   data        = my_lipid_data,
#   engine      = "fgsea",
#   fgsea_rank  = "logFC"
# )
# 
# # Alternative: LIMMA t-statistic (requires a 't' column)
# result_t <- easyLSEA(
#   data        = my_lipid_data,
#   engine      = "fgsea",
#   fgsea_rank  = "t_stat"
# )

## ----thresholds---------------------------------------------------------------
# result <- easyLSEA(
#   data      = my_lipid_data,
#   min_n     = 5L,      # require at least 5 lipids per set
#   n_perm    = 5000L,   # more permutations for DS_perm_pval
#   fgsea_nperm = 20000L # more permutations for fgsea
# )

## ----min-rank-----------------------------------------------------------------
# # Default: include all except P and NA
# result_all <- easyLSEA(data = my_lipid_data, min_rank = "E")
# 
# # Strict: include only high-confidence annotations (A and B)
# result_strict <- easyLSEA(data = my_lipid_data, min_rank = "B")
# 
# # Or apply directly to parse_lipid_chains
# chains_strict <- parse_lipid_chains(annotated, min_rank = "B")
# table(chains_strict$summary$status)

## ----session, eval = TRUE-----------------------------------------------------
sessionInfo()