--- a
+++ b/vignettes/Tweedieverse-vignette.md
@@ -0,0 +1,96 @@
+Tweedieverse: Differential analysis of omics data based on the Tweedie distribution
+================
+Himel Mallick, Ali Rahnavard
+2022-05-03
+
+-   [Introduction](#introduction)
+-   [Installation](#installation)
+-   [Basic Usage](#basic-usage)
+-   [Input](#input)
+-   [Output](#output)
+-   [Getting Started with Tweedieverse](#getting-started-with-tweedieverse)
+-   [Citation](#citation)
+-   [Issues](#issues)
+
+<!-- Himel Mallick -->
+<!-- 2021-03-03 <img src="docs/logo.jpg" align="right" width="365px"/> -->
+Introduction
+------------
+
+Tweedieverse is an R package for differential analysis of omics data implementing a range of statistical methodology based on the [Tweedie distribution](https://en.wikipedia.org/wiki/Tweedie_distribution).
+
+Unlike traditional single-omics tools, Tweedieverse is technology-agnostic and can be applied to both count and continuous measurements arising from diverse high-throughput technologies (e.g., transcript abundances from bulk and single-cell RNA-Seq studies in the form of UMI counts or non-UMI counts, microbiome taxonomic and functional profiles in the form of counts or relative abundances, and compound abundance levels or peak intensities from metabolomics and other mass spectrometry-based experiments, among others).
+
+The software includes multiple analysis methods (e.g., self-adaptive, zero-inflated, and non-zero-inflated statistical models) as well as multiple customization options such as the inclusion of random effects and multiple covariates along with several data exploration capabilities and visualization modules in a unified estimation umbrella.
+
+Installation
+------------
+
+To install the latest release version of `Tweedieverse` from [CRAN](https://cran.r-project.org/) (**not yet available**) run the following command:
+
+``` r
+install.packages("Tweedieverse")
+library(Tweedieverse)
+```
+
+Alternatively, the latest development version of `Tweedieverse` can be loaded using the following command (execute from within a fresh R session):
+
+``` r
+install.packages('devtools')
+library(devtools)
+devtools::install_github("himelmallick/Tweedieverse")
+library(Tweedieverse)
+```
+
+After installing `Tweedieverse`, please make sure the following package versions are also installed (a prerequisite for zero-inflated Tweedie models):
+
+``` r
+devtools::install_version("statmod", version = "1.4.33", repos ="http://cran.us.r-project.org")
+```
+
+``` r
+devtools::install_version("cplm", version = "0.7-8", repos = "http://cran.us.r-project.org")
+```
+
+Basic Usage
+-----------
+
+``` r
+Tweedieverse(features, metadata, output)
+```
+
+Input
+-----
+
+Tweedieverse requires two input files:
+
+-   **features**: A data frame of omics features such as taxa, genes, transcripts, metabolites, etc.
+-   **metadata**: A data frame of metadata to be associated.
+
+For full options, check out the [user manual](https://github.com/himelmallick/Tweedieverse/tree/master/vignettes) or type `?Tweedieverse` in your R console.
+
+Output
+------
+
+A data frame containing coefficient estimates, p-values, and q-values (multiplicity-adjusted p-values) are returned, along with other parameter estimates from the fitted per-feature models.
+
+Getting Started with Tweedieverse
+---------------------------------
+
+Check out the [Tweedie Labs](https://github.com/himelmallick/TweedieLabs/) repository for a collection of walkthrough tutorials (available as source codes, cloud-compatible images, and installable packages) on how to use Tweedieverse with various omics data types.
+
+Citation
+--------
+
+To cite **`Tweedieverse`** in publications, please use:
+
+Mallick H et al. (2021). [Differential Expression of Single-cell RNA-seq Data using Tweedie Models](https://www.biorxiv.org/content/10.1101/2021.03.28.437378v1). bioRxiv, <https://doi.org/10.1101/2021.03.28.437378>.
+
+To cite the **`Tweedieverse`** software, please use:
+
+Mallick H et al. (2021). [Tweedieverse - A Unified Statistical Framework for Differential Analysis of Multi-omics Data](https://github.com/himelmallick/Tweedieverse). R package, <https://github.com/himelmallick/Tweedieverse>.
+
+Issues
+------
+
+We are happy to troubleshoot any issues with the package. Please contact the maintainer via email or [open an issue](https://github.com/himelmallick/tweedieverse/issues) in the GitHub repository.