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Hi,
I have 16S and ITS sequencing data for around 10000 samples. I am trying to find enterotypes by combining both the sequence data. I have calculated the relative abundance for 16S and ITS separately and then combined the OTU tables. The combined OTU table at genus level was used to run DMM script:
I get all NAs in lplc, aic and bic. Is it because I am using relative abundance instead of raw counts or because I am combining 16S and ITS tables? Will it be ok to combine 16S and ITS absolute count table or should I use any other normalization method. Please help.
The text was updated successfully, but these errors were encountered:
Hi,
I have 16S and ITS sequencing data for around 10000 samples. I am trying to find enterotypes by combining both the sequence data. I have calculated the relative abundance for 16S and ITS separately and then combined the OTU tables. The combined OTU table at genus level was used to run DMM script:
taxa <- core_members(pseq_genus_ra, detection = 0.05/100, prevalence = 10/100)
pseq <- prune_taxa(taxa, pseq_genus_ra)
dat <- abundances(pseq)
count <- as.matrix(t(dat))
fit <- lapply(1:10, dmn, count = count, verbose=TRUE)
lplc <- base::sapply(fit, DirichletMultinomial::laplace)
aic <- base::sapply(fit, DirichletMultinomial::AIC)
bic <- base::sapply(fit, DirichletMultinomial::BIC)
I get all NAs in lplc, aic and bic. Is it because I am using relative abundance instead of raw counts or because I am combining 16S and ITS tables? Will it be ok to combine 16S and ITS absolute count table or should I use any other normalization method. Please help.
The text was updated successfully, but these errors were encountered: