README.md

MelonnPan - Model-based Genomically Informed High-dimensional Predictor of Microbial Community Metabolic Profiles

Himel Mallick 2021-02-08

Introduction

MelonnPan is a computational method for predicting metabolite compositions from microbiome sequencing data.

Overview of MelonnPan

MelonnPan is composed of two high-level workflows: MelonnPan-Predict and MelonnPan-Train.

The MelonnPan-Predict workflow takes a table of microbial sequence features (i.e., taxonomic or functional abundances on a per sample basis) as input, and outputs a predicted metabolomic table (i.e., relative abundances of metabolite compounds across samples).

The MelonnPan-Train workflow creates an weight matrix that links an optimal set of sequence features to a subset of predictable metabolites following rigorous internal validation, which is then used to generate a table of predicted metabolite compounds (i.e., relative abundances of metabolite compounds per sample). When sufficiently accurate, these predicted metabolite relative abundances can be used for downstream statistical analysis and end-to-end biomarker discovery.

How to Install

Before installing MelonnPan, please install the prequisites as follows (execute from within a fresh R session):

devtools::install_version("GenABEL.data", version = "1.0.0", repos = "http://cran.us.r-project.org")
devtools::install_version("GenABEL", version = "1.8-0", repos = "http://cran.us.r-project.org")

Once these packages are installed, there are three options for installing MelonnPan:

From Within R

You can install MelonnPan using the devtools package in R using either install_github or install_bitbucket function calls:

devtools::install_github("biobakery/melonnpan")
devtools::install_bitbucket("biobakery/melonnpan")

From Bitbucket (Directly)

Clone the repository using git clone, which downloads the package as its own directory called melonnpan.

git clone https://<your-user-name>@bitbucket.org/biobakery/melonnpan.git

Then, install MelonnPan using R CMD INSTALL.

R CMD INSTALL melonnpan

From GitHub (Directly)

Clone the repository using git clone, which downloads the package as its own directory called melonnpan.

git clone https://github.com/biobakery/melonnpan.git

Then, install MelonnPan using R CMD INSTALL.

R CMD INSTALL melonnpan

Usage

MelonnPan can be run from the command line or from within R. Both methods require the same arguments, have the same options, and use the same default settings. Check out the MelonnPan tutorial for an example application.

Input

Output

References

Zou H, Hastie T (2005). Regularization and Variable Selection via the Elastic Net. Journal of the Royal Statistical Society. Series B (Methodological) 67(2):301–320.

Franzosa EA et al. (2019). Gut microbiome structure and metabolic activity in inflammatory bowel disease. Nature Microbiology 4(2):293–305.

Citation

Mallick H, Franzosa EA, McIver LJ, Banerjee S, Sirota-Madi A, Kostic AD, Clish CB, Vlamakis H, Xavier R, Huttenhower C (2019). Predictive metabolomic profiling of microbial communities using amplicon or metagenomic sequences. Nature Communications 10(1):3136-3146.



biobakery/melonnpan documentation built on May 17, 2021, 3:27 a.m.