@@ -68,29 +68,13 @@ The 3 different graphs generated by **BioFlow-Insight** are :
...
@@ -68,29 +68,13 @@ The 3 different graphs generated by **BioFlow-Insight** are :
### Input
### Input
In this example, we are going to use the **BioFlow-Insight** source code. After cloning both repositories (this one and the rnaseq-nf workflow). We can run the following command to run the analyses (the different steps are described below) :
In this example, we are going to use the **BioFlow-Insight** tool to analyse the rna-seq workflow. After installing **BioFlow-Insight** via pip, and cloning the the rnaseq-nf repository. Simply run this command line :
1. line 1 to 5 : import the `Workflow` object allowing the analysis
```
2. line 6 : create the object `w` corresponding to `Workflow`
bioflow-insight rnaseq-nf/main.nf
1. line 6 : the first parameter is the address of the main Nextflow file (obligatory paramter).
```
2. line 6 : parameter `duplicate` (by default `False`), in the case some processes and subworkflows are duplicated in the workflow by the `include as` option, this parameter will duplicate the elements in the graphs.
3. line 6 : parameter `display_info` (by default `True`), shows the files which are being analysed
3. line 7 : `initialise` runs the entire analysis of the Nextflow workflow
4. line 8 : `generate_all_graphs` generates all the graphs in the mermaid and dot formats + the associated metadata for the graphs
1. line 8 : parameter `render_graphs` (by default `True`), if true the png images of the dot graphs are generated thanks to Graphviz. For large workflows this can sometimes fail (depending on the hardware).
2. line 8 : parameter `processes_2_remove` (by default `[]`), is a list of processes which are to be removed from the graphs. This is usefull in the cas of `MULTIQC` processes (they don't really serve a functionnal role but can cluter the structure since they are connected to the majority of processes).