How to filter v4-v5 16s reads based on E. coli pure culture in qiime2

I need another filtering after dada2, but this time, based on E. coli positive used with my samples.

I am expecting to get pure and identical reads in my E. coli pure culture. However there are still other reads in there and that dada2 did not remove.

Do you have any idea which command to use that will remove the erroneous reads from all my samples in relation to E. coli reads?

I did not find anything in the tutorials about this specific filtering and any help is highly appreciated.

Thanks a lot.

Hi, I don’t know if it is what you are looking for but you can use like a core feature and choose 90,95 or 100%, download tsv with unic names and filter your table to keep only this features.

thanks timanix for your swift reply,
I did not get what you exactly mean by core feature, would that be possible to explain that further?


As I understood, you want to get rid of some “noise” in your samples and leave only the reads of bacteria by your choice. If you will perform core analysis, you will find features that counted, for example, in 50%, 55% and so on to 100% of samples. You can choose the tsv file which contains the list of features, which are counted in corresponding % of your samples. You can then filter your table to remove everything from your samples except included in your list. But I am not sure what you want to do with your samples, maybe I misunderstood you

Thanks a lot, I need to remove a noisy reads from all my samples without discarding the samples, to do that do I need to filter based on seq.qza or taxonomy.qza, or table.qza?

I want to remove all sequences present in the positive and that shouldn’t be there also removing that reads from all my samples I do not know how to fix the --p-min-features threshold.
Do you think I need to use this below command?
qiime feature-table filter-samples
–i-table table.qza
–p-min-features 10
–o-filtered-table feature-contingency-filtered-table.qza

Thanks a lot for your help.

With this command you will delete all samples which contains less than 10 features. It is definitely not what you wanted to do.
If you want to delete features, not samples, you can use

qiime feature-table filter-features
–i-table table.qza
–p-min-frequency 10
–o-filtered-table feature-frequency-filtered-table.qza

to delete all features that counted in all samples less than 10, or

qiime feature-table filter-features
–i-table table.qza
–p-min-samples 2
–o-filtered-table sample-contingency-filtered-table.qza

to remove all features which encountered only in one sample.

But I am afraid it will not help you with

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