RNASeq | Download the RNAseq pipeline | Genomics library

I managed to solve this problem with some trial and error method.

Indeed, it is impossible to obtain a single scalar from a correlation between two unequal-sized matrices.

In fact, the correlation in this function is not conducted on genes at all! It is calculated on the results of a 50-components-PCA of the dataset!

After conducting PCA, you'll have to average the values of every component for each cell type (because each cell type contains different number of cells). Thus, you'll get a single vector (1*50) for each cell type.

You will finally have a dataframe where each column is a different cell type and each row is the average component of the PCA for each cell type.

The calculation of the pearson correlation can be simply achieved using the corr() function of pandas on the final averaged PCA dataframe.

The arrangement of the plot, including dendrogram, can be achieved with seaborn's clustermap() function.

That's it :)

Looking at youre gene_count data, it doesn't have a column for the SAMPID, those were imported as row names. We'll convert them to an actual column, replace the "." with "-" so they match the braindata format, and then we can join. Your sample data doesn't have any elements in common so I use a full_join, but you may prefer a left, right, or inner join--I'm not really sure what your use case is.

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

Do you want:

What do you need the third table for when you can get all the required information from Table 1 and Table 2? Use full_join to merge Table 1 and Table 2 and get the required result shown below

You need to create the first channel with a value factory which never exhausts the channel.

Your linked example implicitly creates a value channel which is why it works. The same happens when you call .collect() on A.out.foo.

Channel.from (or the more modern Channel.of) create a sequence channel which can be exhausted which is why both A and B only run once.

So

The expand function returns a list. By setting the input files to a list instead of a string, you are confusing the script. For defining r1 and r2, you should use something that returns a string instead. I would suggest the string's format() function or an f-string.

Change:

If you know the layout beforehand, then the easiest way would be to store it in some variable, something like this (or alternatively you read this from a config file into a dictionary):