SHAMAN is dedicated to metagenomic analysis, it includes the normalization, the differential analysis and mutiple visualization.
SHAMAN is based on DESeq2 R package [Anders and Huber 2010](http://www.ncbi.nlm.nih.gov/pubmed/20979621) for the analysis of metagenomic data, as suggested in [McMurdie and Holmes 2014](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974642/) and [Jonsson2016](http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4727335/).
SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2 [Love 2014](http://www.ncbi.nlm.nih.gov/pubmed/25516281).
Resulting p-values are adjusted according to the Benjamini and Hochberg procedure [Benjamini and Hochberg 1995].
The PCOA is performed with the ade4 R package and plots are generated with ggplot2 or D3.js packages.
A presentation about SHAMAN is available [here](www/shaman_presentation.pdf).
SHAMAN is compatible with standard formats for metagenomic analysis. We also provide a complete pipeline for OTU picking and annotation named [MASQUE](https://github.com/aghozlane/masque) used in production at Institut Pasteur.
Hereafter is the global workflow of the SHAMAN application:
<imgsrc="www/Workflow.png"align="center"/>
## Installation
SHAMAN is available for R>3.X. The installation, download and execution can all be performed with a small R script :
```
# Load shiny packages
if(!require('shiny')){
install.packages('shiny')
library(shiny)
}
# Install dependencies, download last version of SHAMAN from github and run shaman in one command :
p("SHAMAN is a SHiny application for Metagenomic ANalysis including the normalization,
the differential analysis and mutiple visualization.",style="font-family: 'times'; font-si16pt"),
p("SHAMAN is based on DESeq2 R package",a("[Anders and Huber 2010]",href="http://www.ncbi.nlm.nih.gov/pubmed/20979621"),"for the analysis of metagenomic data, as suggested in",a("[McMurdie and Holmes 2014]",href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974642/"),
". SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2",a("[Love 2014,",href="http://www.ncbi.nlm.nih.gov/pubmed/25516281"),a("Jonsson2016]",href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4727335/"),".
p("SHAMAN is based on DESeq2 R package",a("[Anders and Huber 2010]",href="http://www.ncbi.nlm.nih.gov/pubmed/20979621"),"for the analysis of metagenomic data, as suggested in",a("[McMurdie and Holmes 2014,",href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974642/"),a("Jonsson2016]",href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4727335/"),
". SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2",a("[Love 2014]",href="http://www.ncbi.nlm.nih.gov/pubmed/25516281"),".
Resulting p-values are adjusted according to the Benjamini and Hochberg procedure [Benjamini and Hochberg 1995].
The PCOA is performed with the",a("ade4 R package",href="http://pbil.univ-lyon1.fr/ade4/"),"and plots are generated with",a("ggplot2",href="http://ggplot2.org/"),"or",a("D3.js packages",href="http://d3js.org/"),".
A presentation about SHAMAN is available",a("here.",target="_blank",href="shaman_presentation.pdf"),style="font-family: 'times'; font-si16pt"),
A presentation about SHAMAN is available",a("here.",target="_blank",href="shaman_presentation.pdf"),br(),
"SHAMAN is compatible with standard formats for metagenomic analysis. We also provide a complete pipeline for OTU picking and annotation named",a("MASQUE",href="https://github.com/aghozlane/masque"),"used in production at Institut Pasteur.",style="font-family: 'times'; font-si16pt"),
p("Hereafter is the global workflow of the SHAMAN application:"),
p("SHAMAN is available for R>3.X. The installation, download and execution can all be performed with a small R script :",style="font-family: 'times'; font-si16pt"),