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---
title: "MicrobiomeStat: Comprehensive & Longitudinal Microbiome Analysis in R"
output: github_document
editor_options:
markdown:
wrap: sentence
---
<p align="center" style="margin:0; padding:0;">
<img src="man/figures/logo.png" alt="MicrobiomeStat Logo" width="400" style="margin:0; padding:0;"/>
</p>
<!-- badges: start -->
[](https://cran.r-project.org/package=MicrobiomeStat)
[](https://cran.r-project.org/package=MicrobiomeStat)
[](https://www.gnu.org/licenses/gpl-3.0)
<!-- badges: end -->
The `MicrobiomeStat` package is a state-of-the-art R tool with a **special focus on the analysis of longitudinal microbiome data**. While capable of handling multi-omics data and cross-sectional studies, its **core strength lies in its proficiency in longitudinal analysis**. This makes it an invaluable resource for researchers conducting extensive biological studies over time.
# Citations {#citations}
## General Citation for MicrobiomeStat
If you are using features beyond the `linda` and `linda.plot` functions, please cite as follows, until a preprint version is published:
```
@Manual{,
title = {MicrobiomeStat: Comprehensive Statistical and Visualization Methods for Microbiome and Multi-Omics Data},
author = {Xianyang Zhang and Jun Chen and Caffery(Chen) Yang},
year = {2023},
note = {R package version 1.1.1},
url = {www.microbiomestat.wiki},
}
```
## Special Citation for `linda` and `linda.plot` Functions
If you are using `linda` or `linda.plot` functions, please cite the following paper:
```
Zhou, H., He, K., Chen, J. et al. LinDA: linear models for differential abundance analysis of microbiome compositional data. Genome Biol 23, 95 (2022). https://doi.org/10.1186/s13059-022-02655-5
```
We will update the citation guidelines as soon as the preprint is published.
## Important Note on CRAN Version {#cran-version-note}
Due to the **ongoing development cycle**, the **most up-to-date features** of `MicrobiomeStat` have **not yet been uploaded to the CRAN repository**. The current CRAN version **only supports the `linda` and `linda.plot` functions**. If you **require additional functionalities**, particularly for **analyzing longitudinal data**, we recommend **installing the development version from GitHub**. To do this, you'll first need to **install the `devtools` package** if you haven't already:
```R
install.packages("devtools")
```
Once `devtools` is installed, you can install `MicrobiomeStat` from GitHub using the following command:
```R
devtools::install_github("cafferychen777/MicrobiomeStat")
```
# Table of Contents
1. [Online Tutorials](#online-tutorials)
2. [Benefits of Using MicrobiomeStat](#why-choose-microbiomestat)
3. [Key Features](#features-at-a-glance)
4. [Assistance & Contact Information](#support-contact)
5. [Join Our Discord Community](#discord-community)
6. [Share and Connect](#share-and-connect)
# Online Tutorials {#online-tutorials}
`MicrobiomeStat` represents a comprehensive toolset for microbiome data analysis, boasting extensive capabilities from data input to visualization.
For an in-depth understanding of `MicrobiomeStat`, we have curated a comprehensive online tutorial using GitBook, encompassing:
- Comprehensive **installation and configuration** guidance
- **Analysis walkthroughs** driven by real-world cases
- Hands-on code examples
- Detailed guides on result **interpretation and visualization**
- Frequently Asked Questions
For a seamless experience with `MicrobiomeStat`, we recommend acquainting yourself with these online tutorials:
**MicrobiomeStat Tutorials:** [https://www.microbiomestat.wiki](https://www.microbiomestat.wiki)
## Benefits of Using MicrobiomeStat {#why-choose-microbiomestat}
The field of microbiome research is complex and rapidly evolving. The analytical tools chosen can have significant implications for research outcomes. In this context, `MicrobiomeStat` presents itself as a robust option.
### Comparative Overview
For a thorough understanding of how `MicrobiomeStat` measures against other tools, we've provided detailed comparisons on our website:
- [Comparison with Other Longitudinal Packages](https://www.microbiomestat.wiki/introduction/microbiomestat-versus-the-competition-a-comparative-overview/microbiomestat-vs.-other-longitudinal-packages-an-in-depth-comparison)
- [Comparison with Integrated Analysis Packages](https://www.microbiomestat.wiki/introduction/microbiomestat-versus-the-competition-a-comparative-overview/microbiomestat-vs-integrated-analysis-packages-a-feature-comparison)
### User Support
`MicrobiomeStat` is designed with users in mind. Comprehensive **documentation and tutorials** are available to assist both novice and experienced researchers.
### Ongoing Development
Ensuring that `MicrobiomeStat` remains a leading tool in its category requires **ongoing development**. We're dedicated to regular updates and addressing user feedback.
### Collaborative Development
`MicrobiomeStat` is an open-source tool, and we value contributions from the community. If you have suggestions or improvements, **pull requests are welcomed**.
### Conclusion
`MicrobiomeStat` aims to be a reliable and efficient tool for microbiome data analysis. For those who value **open-source collaboration**, we invite you to be part of our community and contribute to its continuous improvement.
## Key Features {#features-at-a-glance}
| Feature | Description |
|---|---|
| Data Import and Conversion | Supports numerous input formats from popular tools like QIIME2, Mothur, DADA2, Phyloseq and more |
| Cross-sectional Study Analysis | Performs comprehensive analysis of cross-sectional studies |
| Paired Sample Analysis | Excellent tool for analyzing **paired samples** |
| Longitudinal Study Analysis | Allows for exploring the **temporal dynamics** of the microbiome |
| Visualization Capabilities | Offers a wide variety of **visualization styles** |
| Data Export | Supports export of analysis results in diverse formats |
| Ongoing Development | Continual **feature refinement** and **new functionality** addition |
## Assistance & Contact Information {#support-contact}
For assistance or inquiries, feel free to reach out to:
| Name | Email |
|-------------|-----------------------------------------------|
| [Dr. Jun Chen](https://scholar.google.com/citations?user=gonDvdwAAAAJ&hl=en) | [Chen.Jun2@mayo.edu](mailto:Chen.Jun2@mayo.edu) |
| [Chen Yang](https://cafferyyang.owlstown.net/) | [cafferychen7850@gmail.com](mailto:cafferychen7850@gmail.com) |
## Engage in Our Discord Community {#discord-community}
Join our Discord community to stay abreast of the latest developments in `MicrobiomeStat`, engage in discussions, and avail support:
[Join the MicrobiomeStat Discord Server!](https://discord.gg/BfNvTJAt)
Our active community fosters an environment of **collaboration, feedback, and continuous learning**.
## Share and Connect {#share-and-connect}
Spread the word about `MicrobiomeStat` and stay connected through various platforms!
[](https://twitter.com/intent/tweet?url=https%3A%2F%2Fgithub.com%2Fcafferychen777%2FMicrobiomeStat&text=Check%20out%20this%20awesome%20package%20for%20comprehensive%20and%20longitudinal%20microbiome%20analysis%20in%20R!)
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[](https://www.linkedin.com/shareArticle?mini=true&url=https%3A%2F%2Fgithub.com%2Fcafferychen777%2FMicrobiomeStat&title=Check%20out%20this%20awesome%20package%20for%20comprehensive%20and%20longitudinal%20microbiome%20analysis%20in%20R!)
[](https://www.reddit.com/submit?url=https%3A%2F%2Fgithub.com%2Fcafferychen777%2FMicrobiomeStat&title=Check%20out%20this%20awesome%20package%20for%20comprehensive%20and%20longitudinal%20microbiome%20analysis%20in%20R!)