The goal of omicsTools is to provide tools for processing and analyzing omics data from genomics, transcriptomics, proteomics, and metabolomics platforms. It provides functions for preprocessing, normalization, visualization, and statistical analysis, as well as machine learning algorithms for predictive modeling. omicsTools is an essential tool for researchers working with high-throughput omics data in fields such as biology, bioinformatics, and medicine.
License: MIT + file LICENSE
You can install the Stable version of omicsTools like so:
install.packages("omicsTools")
To get a bug fix, or use a feature from the development version, you can install omicsTools from GitHub.
if (!require("devtools", quietly = TRUE))
install.packages("devtools")
devtools::install_github("YaoxiangLi/omicsTools")
You can also use the graphical user interface:
# Load the CSV data
data_file <- system.file("extdata", "example1.csv", package = "omicsTools")
data <- readr::read_csv(data_file)
#> Rows: 85 Columns: 482
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (1): Sample
#> dbl (414): Urea_pos, Lipoamide_pos, AcetylAmino Sugars_pos, Glycerophosphoch...
#> lgl (67): DBQ_pos.IS, Aminolevulinic Acid_pos, Leucine_pos, Homocystine_pos...
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
# Apply the impute function
imputed_data <- omicsTools::impute(data, percent = 0.2)
#> 280 features removed by percent of missing values > 0.2
# Write the imputed data to a new CSV file
readr::write_csv(imputed_data, paste0(tempdir(), "/imputed_data.csv"))
You can also use the graphical user interface:
# Load the CSV data
data_file <- system.file("extdata", "example2.csv", package = "omicsTools")
data <- readr::read_csv(data_file)
#> Rows: 63 Columns: 202
#> ── Column specification ────────────────────────────────────────────────────────
#> Delimiter: ","
#> chr (1): Sample
#> dbl (201): Urea_pos, Lipoamide_pos, Glycerophosphocholine_pos, Allanoate_pos...
#>
#> ℹ Use `spec()` to retrieve the full column specification for this data.
#> ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
# Apply the normalize function
normalized_data <- omicsTools::normalize(data)
# Write the normalized data to a new CSV file
readr::write_csv(normalized_data, paste0(tempdir(), "/normalized_data.csv"))
You can also use the graphical user interface:
library(omicsTools)
#>
#> This is omicsTools version 1.0.5.
#> omicsTools is free software and comes with ABSOLUTELY NO WARRANTY.
#> Please use at your own risk.
omicsTools::run_app()
devtools::build_readme()
Since this is a collaborative project, please adhere to the following code formatting conventions: * We use the tidyverse style guide (https://style.tidyverse.org/) * Please write roxygen2 comments as full sentences, starting with a capital letter and ending with a period. Brevity is preferred (e.g., “Calculates standard deviation” is preferred over “This method calculates and returns a standard deviation of given set of numbers”).