Is it possible to use isOnclust on multiple samples?
DesmondoDekker opened this issue · comments
Hi!
I am working with samples from nanopore. I successfully used isOnclust on a single sample, but I would need to compare various samples. Is it possible to use isOnclust on multiple samples?
It depends on what your input data is and what is the desired output of the analysis.
Are all the reads within one file but with sample-specific barcods? maybe then perform an initial barcode clustering/trimming with e.g. pychopper, and the run isONclust on each of the sample specific files.
Otherwise please describe the data and the desired outcome in more detail.
Hi, thank you very much for your prompt answer.
I have 10 different singles file.fastq.
I would like to use isOnclust, but then I would like to compare one sample against another one. The point is that if i run isOnclust on every single sample, I do not know how to compare the clusters across the samples. Brefly, I would like only one "otu table" with 10 samples.
I hope I have been clear.
Thanks a lot
Not sure it is possible to create an OTU table without some scripting. One idea:
- Label all your reads in the headers (sample 1 gets a
_1
appended, etc) for uniqueness. - Combine all reads into one big file.
- Cluster the big file with isONclust.
- Parse the isonclust csv output file. The file contains a line for each read and which 'cluster representative' it is part of. Summing the reads per sample from this file, it will give you the abundance of each sample in a cluster.
It sounds good.
Thanks for the suggestion!