Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

quantitative metabarcoding no NORMALIZATION #89

Open
csmiguel opened this issue Oct 11, 2023 · 0 comments
Open

quantitative metabarcoding no NORMALIZATION #89

csmiguel opened this issue Oct 11, 2023 · 0 comments

Comments

@csmiguel
Copy link

Hi,
I want to use metagenomeSeq for DA analysis for a dataset that has already been normalized according to an internal standard in the library. That means, that I am interested not only in relative changes but also in absolute changes of reads (abundances) between different treatments in my experiment. I would like to know if the model implemented in fitFeatureModel() can be used with this quantitative approach of feature counts without any normalization. Since fitFeatureModel() requires the normFactors slot to be filled, would it be appropriate for my approach to add a constant integer of size equal to number of samples? (eg, normFactors(obj) <- rep(1, ncol(obj)))
Thanks

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant