OPM and its Helper Packages


The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. The phenotypic reaction of single-celled organisms such as bacteria, fungi, and animal cell cultures to up to 2,000 environmental challenges can be recorded on sets of 96-well microtiter plates.

The opm package for the free statistical software environment R offers tools for storing the curve kinetics, aggregating the curve parameters, recording associated metadata of organisms and experimental settings as well as methods for analyzing these highly complex data sets graphically and statistically. The package also includes 95% confidence plots, enhanced heatmap graphics and customized multiple comparisons of means procedures for comparing the estimated curve parameters. It is also possible to discretize these parameters and to export them for investigations with other programs and for generating reports for taxonomic journals such as IJSEM. Export and import in the YAML, JSON or CSV format facilitates the data exchange among labs. The CSV files produced by the OmniLog® reader can not only be easily imported but also batch-converted in large numbers.

The opm package for R is a comprehensive software for analysing phenotype microarray and growth-curve data. For more information, see the opm R-Forge site or the main tutorial for opm.


The package can be used on Windows, Mac and Linux/UNIX systems. As a prerequisite, one needs to obtain the statistical computing environment R. We also recommend a graphical user interface such as RStudio. Both are freely available; instructions for installation are given on their websites. Maria del Carmen Montero-Calasanz has compiled a detailed description of the installation of opm etc. under Windows. The shown use of graphical user interfaces is similar on other systems.

There are three ways to install opm and its dependencies. The first way is to visit the opm R-Forge site, download the source files or Windows binaries and install them locally. Alternatively, at the R prompt, enter:


You will then be asked for what exactly to install. In our experience this works well under Windows, if otherwise please let us know. (But please first see the troubleshooting section.) Third, opm and its helper packages can be downloaded using the links further below on this page and installed manually (and optionally checked beforehand). Documentation comes with the packages but is also linked below.


The only somewhat more frequently encountered problems we are aware of when attempting to install opm and its dependencies are the following.

Outdated R environment
There is only one solution to this problem, to download and install a newer version of R. Detailed instructions on how to do this are given elsewhere.
Outdated R packages
Outdated R packages on which opm or the installation script depend hinder the installation. To solve this we recommend biocLite as a convenient tool to install not only Bioconductor but also core packages, and to update many packages at once. To use biocLite just copy and paste the code snippet shown there into the R prompt.
Rtools on Windows
Rtools is not needed to install the opm package (not even under Windows), but we have observed that old Rtools versions might yield errors with the opm installation script. If so, either deinstall or upgrade Rtools before running the script.

In the case of errors that cannot be resolved, please send us the complete output generated when loading the installation file.


Using opm the main tutorial for opm, the best starting point for new users
Substrate information in opm availability and use of data on phenotype microarray substrates in opm
Growth curves in opm applying opm not to phenotype microarray data but to growth curves

All Package Documentation

pkgutils comprehensive online documentation of the latest pkgutils version
opm comprehensive online documentation of the latest opm version
opmdata comprehensive online documentation of the latest opmdata version
opmextra comprehensive online documentation of the latest opmextra version

Miscellaneous Documentation

RStudio notes on the use of RStudio
Fact Sheet fact sheet summarizing the main features of opm
ISME 2012 our poster presented at the ISME 14 conference
SRI 2013 our talk at the Conference on Predicting Cell Metabolism and Phenotypes
Workshop our introduction to the opm workshop at the 2015 Phenotype Microarray conference in Florence
DSMZ opm introduction at DSMZ


pkgutils built and checked R source-code archive of the latest pkgutils version
opm built and checked R source-code archive of the latest opm version
opmdata built and checked R source-code archive of the latest opmdata version
opmextra built and checked R source-code archive of the latest opmextra version

Last Update

The last change to the packages or their documentation has been made on Fri Jul 26 03:07:35 CEST 2019.


We thank the authors and maintainers of the R packages on which pkgutils, opm and opmdata depend and of those packages used to generate this documentation. Helpful feedback from opm users is gratefully acknowledged.


Overview on opm Lea A.I. Vaas, J. Sikorski, B. Hofner, N. Buddruhs, A. Fiebig, H.-P. Klenk and M. Göker. "opm: An R package for analysing OmniLog® Phenotype MicroArray Data". Bioinformatics 29 (14): 1823-1824, 2013.
Parameter comparison and visualization with opm Lea A.I. Vaas, J. Sikorski, V. Michael, M. Göker and H.-P. Klenk. "Visualization and curve-parameter estimation strategies for efficient exploration of phenotype microarray kinetics". PLoS ONE 7 (4): e34846, 2012.
Advanced usage of opm to detect differential expressions B. Hofner, L. Boccuto and M. Göker. "Controlling false discoveries in high-dimensional situations: Boosting with stability selection". BMC Bioinformatics 16 (6): 144, 2015.


The pkgutils, opm and opmdata packages are free software published under the GPL and come with absolutely no warranty. This holds even though a lot of effort was invested into getting the packages free of bugs.


For contact addresses see the R-Forge site.