MultiQC | Aggregate results from bioinformatics analyses | Genomics library

I think it's due to you used expand function in a wrong way, expand only accepts two positional arguments, where the first one is pattern and the second one is function (optional). If you want to supply multiple patterns you should wrap these patterns in list.

After some studying on source code of snakemake, it turns out expand function doesn't check if user provides < 3 positional arguments, there is a variable combinator in if-else that would only be created when there are 1 or 2 positional arguments, the massive amount of positional arguments you provide skip this part and lead to the error when it tries to use combinator later.

Source code: https://snakemake.readthedocs.io/en/v6.5.4/_modules/snakemake/io.html

First, glob_wildcards(INPUTDIR + "{basenames}_R1.fastq.gz") returns a Wildcards object that contains the key:value pair for each wildcard. If you want to get the basenames, it should be glob_wildcards(INPUTDIR + "{basenames}_R1.fastq.gz").basenames

Second, I assume all fastq.gz files are generated by decompress_h1n1 checkpoint, since you already include the fastqc output in aggregate_decompress_h1n1 function. You shouldn't include those outputs again in rule all, it leads to snakemake try to do fastqc before checkpoint got executed.

Third, you should also put your trim_qc outputs in the aggregate_decompress_h1n1 function, basically it's the same issue as fastqc, probably the same for salmon related rules too.

There might be a potential issue, I noticed you use wrapper for fastqc, I remember that official fastqc wrapper requires the output must have html and zip, while you have a raw prefix. But I didn't see a 0.80.3 release in official document, not sure if you are using some other repository to access wrapper

From your comments I gather that what you really want to do is run a flexibly configured number of QC methods and then summarise them in the end. The summary should only run, once all the QC methods you want to run have completed.

Rather than forcing the MultiQC rule to be executed in the end, manually, you can set up the MultiQC rule in such a way that it automatically gets executed in the end - by requiring the QC method's output as input.

Your goal of flexibly configuring which QC rules to run can be easily achieved by passing the names of the QC rules through a config file, or even easier as a command line argument.

Here is a minimal working example for you to extend:

I think gcd was moved to the math pack in 3.9. See https://docs.python.org/3/library/fractions.html

Changed in version 3.9: The math.gcd() function is now used to normalize the numerator and denominator. math.gcd() always return a int type. Previously, the GCD type depended on numerator and denominator.

I suggest you create a virtual environment with 3.8 and try that. There are tons of tutorials on how to do this.

In your rule all you have:

You could give to the input of multiqc rule the files produced by the individual QC rules. In this way, multiqc will start once all those files are available. E.g.:

All output files need to have same wildcards, or else it would cause conflict in resolving job dependencies. Not all files in output: have {rRNAdb} wildcard, which is causing this problem. For example, if you have two {rRNAdb} values, both would write to file "{OUTDIR}/temp/{sample}.fastq", which snakemake correctly doesn't allow.