SIAMCAT is a pipeline for Statistical Inference of Associations between
Microbial Communities And host phenoTypes. A primary goal of analyzing
microbiome data is to determine changes in community composition that are
associated with environmental factors. In particular, linking human microbiome
composition to host phenotypes such as diseases has become an area of intense
research. For this, robust statistical modeling and biomarker extraction
toolkits are crucially needed. SIAMCAT provides a full pipeline supporting
data preprocessing, statistical association testing, statistical modeling
(LASSO logistic regression) including tools for evaluation and interpretation
of these models (such as cross validation, parameter selection, ROC analysis
and diagnostic model plots).
SIAMCAT is developed in the
Zeller group
and is part of the suite of computational microbiome analysis tools hosted at
EMBL.
In order to start with SIAMCAT, you need to install it from Bioconductor:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SIAMCAT")
Alternatively, you can install the current development version via devtools:
require("devtools")
devtools::install_github(repo = 'zellerlab/siamcat')
There are a few manuals that will kick-start you and help you analyse your
data with SIAMCAT. You can find links to those on the
Bioconductor website of SIAMCAT
or you can type into R:
browseVignettes("SIAMCAT")
# Please Note:
# `browseVignettes` only works if `SIAMCAT` has been installed via Bioconductor
If you have any question about SIAMCAT, if you run into any issue,
or if you would like to make a feature request, please:
If you have a more general question (that could be useful to several other users), please do not hesitate to post it on a dedicated forums such as Stackoverflow or Biostars. If you let us know about the question, we will answer it swiftly.
Please consider giving us feedback. (This feedback is useful for us to justify the funding we get for developing and maintaining this package.)
SIAMCAT is distributed under the GPL-3 license.
If you use SIAMCAT, please cite us by using
citation("SIAMCAT")
or by
Wirbel J, Zych K, Essex M, Karcher N, Kartal E, Salazar G, Bork P, Sunagawa S, Zeller G Microbiome meta-analysis and cross-disease comparison enabled by the SIAMCAT machine learning toolbox Genome Biol 22, 93 (2021) https://doi.org/10.1186/s13059-021-02306-1
In this publication, we analyzed a large set of case-control microbiome
datasets. The metadata and taxonomic profiles of these studies are available
through a Zenodo repository:
.
To give you a small preview about the primary package output, here are some
example plots taking from the main SIAMCAT vignette.
In this vignette, we use an example dataset which is also included in
the SIAMCAT package. The dataset is taken from the publication of
Zeller et al, which demonstrated
the potential of microbial species in fecal samples to distinguish patients
with colorectal cancer (CRC) from healthy controls.
The result of the check.associations function is an association plot.
For significantly associated microbial features, the plot shows:
After statistical models have been trained to distinguish cancer cases
from controls, the models can be investigated by the function
model.interpretation.plot. The plots shows:
Several publications already used SIAMCAT (or previous versions thereof).
Original Publication that inspired
SIAMCAT
See Figure 5
See Figure 3 - figure supplement 1
In this publication,
SIAMCATis used extensively for holdout testing
If you used SIAMCAT in your publication,
let us know!