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17 changes: 17 additions & 0 deletions index-metagenomics.md
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Expand Up @@ -63,6 +63,9 @@ We then developed [several tutorials](https://galaxyproject.github.io/training-m

In this tutorial the Standard Operating Procedure (SOP) for MiSeq data, developed by the creators of the Mothur software package, is perfomed within Galaxy.

- [Metatranscriptomics analysis using microbiome RNA-seq data](https://training.galaxyproject.org/training-material/topics/metagenomics/tutorials/metatranscriptomics/tutorial.html)
Metatranscriptomics analysis enables understanding of how the microbiome responds to the environment by studying the functional analysis of genes expressed by the microbiome. In this tutorial, we will analyze time-series data from a microbial community inside a bioreactor.

# Workflows

To orchestrate tools and help users with their analyses, several [workflows](https://asaim.readthedocs.io/en/latest/workflows.html){:target="_blank"} are available. They formally orchestrate tools in a defined order and with defined parameters, but they are customizable (tools, order, parameters).
Expand Down Expand Up @@ -122,6 +125,20 @@ The tools used in the EBI Metagenomics pipeline are also available here and can

However, the parameters must be adjusted by the user as we could not find them in the EBI Metagenomics documentation.

## ASaiM-MT: Optimized workflow for metatranscriptomics data analysis
While the shotgun workflow is suitable for both metagenomics and metatranscriptomics datasets, we also offer an enhanced workflow aimed specifically at metatranscriptomics data.

![](https://asaim.readthedocs.io/en/latest/_images/asaim-mt_workflow.png)

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maybe we should duplicate the images. Not sure if anyone that changes the ASAIM website takes this page into account as well.

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I dont think anybody besides @bebatut and me change ASaiM :P but am happy to add the image here as well to be safe indeed


The workflow is divided into 4 parts:

1. **Preprocessing** - Process raw metatranscriptomics data to perform further analysis.
2. **Taxonomy Quantitation** - Assignment of taxonomy along with abundance values and visualization.
3. **Functional Quantitation** - metabolic assignment of identified functions and gene and pathway abundance annotation.
4. **Taxonomy-Function Quantitation** - combine taxonomy and functional quantitation values into relative abundance values at different levels such as e.g. the abundance of a pathway between phyla.



# References

{% bibliography --cited --prefix index-metagenomics --group_by none %}