[R-sig-ME] info model glmer

Guidantonio Malagoli Tagliazucchi gu|d@nton|o@mt @end|ng |rom gm@||@com
Fri Mar 6 21:30:34 CET 2020


I have a dataset with two main groups (e.g. healthy and disease, column
"status") and inside each group other two groups (status_genomic).  I have
another column with the tissues (tissue). Columns are genomic features.

replicate(40, rnorm(2000)))


Rows are subjects, columns genomic features.

My aim is identifying of the genomic features (genomic_feature) that are
predictive of the status (column status) and status_genomic. For example I
would like to identify the genomic_feature X with  a relation with the
status but also with the status_genomic. From my model I would like to
exclude the effect of the tissue that is a confounder.

I thought to the following model:

my_formula<-as.formula(status ~ genomic_feature1 + genomic_feature2 +
genomic_feature3 [...] + status_genomic + (1 | tissue))

glmer(my_formula, input_df, family= binomial("logit")

I am not totally sure that this is correct (especially for status_genomic).
Do you have any suggestion who you can provide to me to develop a better
model? Sorry for this question, but i am not an expert.

Thanks in advance for the support,


	[[alternative HTML version deleted]]

More information about the R-sig-mixed-models mailing list