knitr::opts_chunk$set(echo = params$printcode)

Print All Selections

for (i in 1:length(params)) {
  if (TRUE) {
    cat(paste0(names(params)[i], ": ", params[[i]], "\n"))
  }
}
devtools::load_all()

LOAD DATA FUNCTIONS

idep_data <- idepGolem::get_idep_data()

expression_file <- data.frame(
  datapath = params$YOUR_DATA_PATH
)
if (!is.null(params$YOUR_EXPERIMENT_PATH)) {
  experiment_file <- data.frame(
    datapath = params$YOUR_EXPERIMENT_PATH
  )
} else {
  experiment_file <- NULL
}
load_data <- input_data(
  expression_file = expression_file,
  experiment_file = experiment_file,
  go_button = FALSE,
  demo_data_file = idep_data$demo_data_file,
  demo_metadata_file = idep_data$demo_metadata_file
)

converted <- convert_id(
  query = rownames(load_data$data),
  idep_data = idep_data,
  select_org = "BestMatch"
)

all_gene_info <- gene_info(
  converted = converted,
  select_org = "BestMatch",
  idep_data = idep_data
)

converted_data <- convert_data(
  converted = converted,
  no_id_conversion = params$no_id_conversion,
  data = load_data$data
)

gene_names <- get_all_gene_names(
  mapped_ids = converted_data$mapped_ids,
  all_gene_info = all_gene_info
)

PRE-PROCESS FUNCTIONS

processed_data <- pre_process(
  data = converted_data$data,
  missing_value = params$missing_value,
  data_file_format = params$data_file_format,
  low_filter_fpkm = params$low_filter_fpkm,
  n_min_samples_fpkm = params$n_min_samples_fpkm,
  log_transform_fpkm = params$log_transform_fpkm,
  log_start_fpkm = params$log_start_fpkm,
  min_counts = params$min_counts,
  n_min_samples_count = params$n_min_samples_count,
  counts_transform = params$counts_transform,
  counts_log_start = params$counts_log_start,
  no_fdr = params$no_fdr
)
# processed_data <- pre_process(
#   data = converted_data$data,
#   missing_value = "geneMedian",
#   data_file_format = 1,
#   low_filter_fpkm = NULL,
#   n_min_samples_fpkm = NULL,
#   log_transform_fpkm = NULL,
#   log_start_fpkm = NULL,
#   min_counts = .5,
#   n_min_samples_count = 1,
#   counts_transform = 1,
#   counts_log_start = 4,
#   no_fdr = NULL
# )

fig.height=1.5, fig.width=2.5

if (params$data_file_format == 1) {
  total_counts_ggplot(
    counts_data = processed_data$raw_counts,
    sample_info = load_data$sample_info
  )
}
# colnames(processed_data$data)

eda_scatter(
  processed_data = processed_data$data,
  # plot_xaxis = "p53_IR_1",
  # plot_yaxis = "p53_mock_1"
  plot_yaxis = colnames(processed_data$data)[1],
  plot_xaxis = colnames(processed_data$data)[2]
)
eda_boxplot(
  processed_data = processed_data$data,
  sample_info = load_data$sample_info
)


espors/idepGolem documentation built on April 23, 2024, 1:11 p.m.