The Ultimate Guide to the tmod Package in R

R Package Guides

Explore valuable documentation and insights to make the most of the tmod package in R. Get ready to unlock the full potential of the tmod package!

Learn R for Free with DataCamp

Master in-demand skills with DataCamp's interactive courses

Start Learning Now

As our partner, DataCamp may pay us a commission at no cost to you for purchases made through this link.

AI-powered R programming assistant

Have questions about the tmod package? Get quick and helpful answers from our cutting-edge AI-powered assistant.

Advance Your Career with Udacity

Take your data and AI skills to the next level with industry-recognized Nanodegree programs

Explore Courses

As our partner, Udacity may pay us a commission at no cost to you for purchases made through this link.

What is the tmod package?

In this section, we’ll delve into the fundamental aspects and key features of the package.

The tmod package provides a range of statistical hypothesis tests and measures for gene set analysis. Its particularly useful in the field of bioinformatics, where it can support the identification of genes associated with a particular phenotype or condition.

Title: Feature Set Enrichment Analysis for Metabolomics and Transcriptomics
Description: Methods and feature set definitions for feature or gene set enrichment analysis in transcriptional and metabolic profiling data. Package includes tests for enrichment based on ranked lists of features, functions for visualisation and multivariate functional analysis. See Zyla et al (2019) .
Author: January Weiner [aut, cre] ()
Maintainer: January Weiner

How to install the tmod package?

In this section, we’ll walk you through the process of installing and loading the tmod package. By following these steps, you can seamlessly add new functions, datasets, and other resources to your R environment for a more robust workflow.

# Install the {Package} package if it's not already installed
if (!require("{Package}")) {
    install.packages("{Package}")
}


# Load the {Package} package
library("{Package}")

Upskill Your Data Science Team with O'Reilly

Access expert-led courses and resources for R programming and beyond

Explore O'Reilly's Library

As our partner, O'Reilly may pay us a commission at no cost to you for purchases made through this link.

What package information should you know?

In this section, we’ll go over the technical aspects of the tmod package.

Key features

Datasets: Many R packages include built-in datasets that you can use to familiarize yourself with their functionalities. To identify built-in datasets. To identify the datasets for the tmod package, visit our database of R datasets.
Vignettes: R vignettes are documents that include examples for using a package. To view the list of available vignettes for the tmod package, you can visit our visit our database of R vignettes.
Citation: Citing R packages in your publications is important as it recognizes the contributions of the developers. To find citation information for the tmod package, visit our database of R package citations.

Technical details

License type: GPL (>= 2.0). For license details, visit the Open Source Initiative website.
Compilation requirements: Some R packages include internal code that must be compiled for them to function correctly. The tmod package does not have compilation requirements.
Required dependencies: A required dependency refers to another package that is essential for the functioning of the main package. The tmod package has the following required dependencies: R (>= 2.10).
Suggested dependencies: A suggested dependency adds extra features to the main package, but the main package can work without it. The tmod package has the following suggested dependencies: testthat, knitr, rmarkdown, dplyr, pander, cowplot.
External dependencies: External dependencies are other packages that the main package depends on for linking at compile time. The tmod package does not use any external sources.
Imported packages: Importing packages allows developers to leverage existing code and functionalities without having to reinvent the wheel. The tmod package has the following imported packages: beeswarm, tagcloud, XML, methods, plotwidgets, RColorBrewer, gplots, tibble, pheatmap, ggplot2, tidyr, purrr, rlang, tidyselect, ggrepel.
Enhancements: Enhancements help developers expand the capabilities of their packages without starting from scratch. The tmod package has no enhancements.

How to get help with the tmod package?

In this section, we’ll discuss a variety of available resources for getting help with the tmod package.

Key resources

The help() function: R’s built-in help system is a handy tool to find documentation. You can use the help("tmod") function to retrieve detailed information, examples, and usage instructions. Alternatively, you can use the ? operator as a shortcut.
Package website: The tmod package has a dedicated website. You can visit: https://tmod.online, https://github.com/january3/tmod/, https://january3.github.io/tmod/.
Developer support: You can email January Weiner . For contact information, visit our R community directory.

Additional resources

AI tools: Use AI programming tools like DataLab to promptly address your questions. (Please note that we may earn a commission if you purchase through this link. By trying DataLab, you help sustain our platform. Thank you for your support!)
Online courses: Try our handpicked collection of R programming courses designed to boost your proficiency in R programming.
Books: Explore our curated selection of R programming books tailored to help you master R programming.
Discussion forums: Online forums are excellent platforms to ask questions, share knowledge, and troubleshoot issues. The most popular forums for R programmers are StackOverflow and Posit Community.

Other package guides

Explore our comprehensive guides for other R packages. These guides are valuable resources for accessing a wide range of information, making it easier to navigate R documentation in one place.

Share the Post: