load_raw: Load raw data

In villegar/MetaPipe: A High-Performance Computing Pipeline for QTL Mapping of Large Ionomic and Metabolomic Datasets

Load raw data

Description

Load raw data from disk and aggregate (using the mean function) observations with duplicated IDs (first column). Non-numeric columns must be excluded using the excluded_columns parameter.

Usage

load_raw(raw_data_filename, excluded_columns = NULL)

Arguments

raw_data_filename	Filename containing the raw data, it can be a relative path (e.g. "my_input.csv") or an absolute path (e.g. "/path/to/my_input.csv").
excluded_columns	Numeric vector containing the indices of the dataset properties that are non-numeric, excluded columns.

Value

Data frame with the pre-processed raw data.

Examples

# Toy dataset
example_data <- data.frame(ID = c(1,2,3,4,5), 
                           P1 = c("one", "two", "three", "four", "five"), 
                           T1 = rnorm(5), 
                           T2 = rnorm(5))
write.csv(example_data, "example_data.csv", row.names = FALSE)
write.csv(example_data[c(1:5, 1, 2), ], 
          "example_data_dup.csv", 
          row.names = FALSE)
knitr::kable(MetaPipe::load_raw("example_data.csv", c(1, 2)))
knitr::kable(MetaPipe::load_raw("example_data_dup.csv", c(1, 2)))


# F1 Seedling Ionomics dataset
ionomics_path <- system.file("extdata", 
                             "ionomics.csv", 
                             package = "MetaPipe", 
                             mustWork = TRUE)
ionomics <- MetaPipe::load_raw(ionomics_path)
knitr::kable(ionomics[1:5, 1:8])

# Clean up example outputs
MetaPipe:::tidy_up("example_data")

villegar/MetaPipe documentation built on Nov. 22, 2022, 10:44 p.m.