EcoMet workflow

Tutorial: Eco-Metabolomics workflow

Following are instructions how to reproduce the results of the study published in [1] & [2].

In the Galaxy welcome screen, click on the "Eco-Metabolomics" entry in the left pane. A list of modules will appear. Click on the module "ecomet_download". This module will download the complete MTBLS520 dataset into your Galaxy history (Fig. 1) [3]. Do not change the value in the field "MetaboLights ID". It is already set to "520" - which is the ID of the dataset in MetaboLights. Please click on the button "Execute" to start the download. It will take several minutes for the download to complete.

Fig. 1.

After the download has been completed successfully (Fig. 2), the modules "ecomet_raw_extract" and "ecomet_qc_extract" import the data from the dataset into Galaxy (Fig. 3). Choose the dataset you have just downloaded as input. When you click on the button "Execute", the data acquired in positive mode will be extracted and imported into the Galaxy history. You can change the polarity to negative here. Make sure that you also select this polarity with subsequent modules or with the workflow.

Fig. 2.

Fig. 3: Data extraction

It will take several minutes to import the data. Next, click on “Shared Data / Workflows” tab on the upper pane. A new screen appears, which shows all workflows shared to you (Fig. 4). In order to process the Eco-Metabolomics workflow, you need to import the workflow. Please click on the small arrow icon in the button "Eco-Metabolomics workflow" and then on "Import". This will import the workflow to your Galaxy history.

Fig. 4: Workflows

After the screen has been reloaded automatically, the just imported workflow should appear in the list under the name "imported: Eco-Metabolomics Workflow". Please click on the entry to "Edit" and get an overview of the entire workflow (Fig. 5).

Fig. 5: Edit and run the Eco-Metabolomics workflow

The window will reload and will show a graphical representation of the entire workflow. The next step is to run the workflow. In order to proceed, click on the little "gear" button in the upper right corner (Fig. 6).

Fig. 6: Run the workflow

On the next screen, select the input variables and input datasets as listed in Fig. 7. Make sure that you have selected the correct input data and variables (e.g. polarity).

Fig. 7: Parameter settings for starting the entire workflow

After you have selected the entries, click on “Run workflow” in the upper right corner (Fig. 7). This will start the computational workflow.

Optional: In case you have selected "negative" mode when extracting the data in step 2 (module "ecomet_raw_extract" and "ecomet_qc_extract", see Fig. 2), please make sure that you also select the corresponding negative mode in the modules "ecomet_preparations" and "ecomet_quality_control" (Fig. 8).

Fig. 8: Polarity options

Following is an overview of the Galaxy workflow for the Eco-Metabolomics dataset (Fig. 9).

Fig. 9: Overview of the entire workflow

The processing of the entire workflow will take about 30 minutes, depending on the resources of the cloud environment.

When the entries in the right pane have become green, you can click on them to see details. A click on the small “eye” icon will open a particular plot or text file of the module.

Publications

[1] Peters, K., Gorzolka, K., Bruelheide, H. & Neumann, S. (2018): Computational workflow to study the seasonal variation of secondary metabolites in nine different bryophytes. Nature Scientific Data. Accepted.

[2] Peters, K., Gorzolka, K., Bruelheide, H. & Neumann, S. (2018): Seasonal variation of secondary metabolites in nine different bryophytes. Ecology and Evolution. https://doi.org/10.1002/ece3.4361.

[3] Peters, K., Gorzolka, K., Bruelheide, H. & Neumann, S. (2018): Seasonal variation of secondary metabolites in 9 different moss and liverwort species. MetaboLights 520. https://www.ebi.ac.uk/metabolights/MTBLS520

[4] Peters, K., Gorzolka, K., Bruelheide, H. & Neumann, S. (2018): Container for the Galaxy workflow to process the MTBLS520 dataset. DockerHub. https://hub.docker.com/r/korseby/mtbls520/

[5] Peters, K., Gorzolka, K., Bruelheide, H., & Neumann, S. (2018). Code for the computational workflow to study the seasonal variation of secondary metabolites in nine different bryophytes using the MTBLS520 dataset (Version v1.1). Zenodo. http://doi.org/10.5281/zenodo.1284246