For this
You can try a few other things:
- Disconnect all noodles, then reconnect in the order of job execution
- Double check that you are merging collections that contain data all with the same datatype. For your case, this would be the txt formatted reports for MultiQC: one merge per report type
- Then, that merged collection is connected to MultiQC, after the section is defined to be a collection and the tool/report type is set
Then for this
This tutorial has a general merge example
- Hands-on: Using dataset collections / Using dataset collections / Using Galaxy and Managing your Data (merge-collections)
And this workflow template includes MultiQC with a merge in the data preparation steps.
- Quality Control Start Here! multQC issue and guidance? - #2 by jennaj << see the workflow template
- Issues with receiving results from FastQC in MultiQC from several collections of samples - #3 by jennaj << screenshots and direct link to the workflow
Notice how I was ensuring that all samples had a unique element identifier (sample name) at the very start. Paired fastq data is a bit different from BAMs and Bigwig data, and involves an extra step to add in forward/reverse notation inside of the workflow, but the basic logic applies to all data: simple, standardize formats for the element identifiers used in the input collections. This makes it easier to manipulate the collections later.
Finally, I have some unsolicited advice
: your workflow contains duplicated processing paths. Could this be simplified? Maybe input all BAMs together, all BigWigs together, run the statistics together, then split out control/case data after into collections (using the element identifiers from a tabular input?) for the downstream MACS2 jobs?
But either way should work. You can welcome to share back a link to your workflow (and screenshots showing what to pay attention to) as you work through this. But try the first items above first please! Thanks! ![]()