Hello,
I am new born in field of bioinformatics and i am glad to using MMUPHin R packages for meta-analysis of gut microbiome 16S sequencing data.
I use this tool to detect different abundance microbes based in different disease states, compare with healthy controls.
I have 3 questions regardless MMPHin tool.
- i run the lm_meta after batch/study correct,
data_meta$Host_case_disease ← relevel(x = as.factor(data_meta$Host_case_disease), ref = “disease_type”)
I have not another variables to check only the different type of disease
fit_lm_meta ← lm_meta(feature_abd = data_abd_adj,
batch = “Bioproject”,
exposure = “Virus”,
covariates = c(“Host_case_disease”),
data = data_meta,
control = list(verbose = FALSE))
meta_fits ← fit_lm_meta$meta_fits
my question is, if someone knows what is mean this warnings ?
Fisher scoring algorithm may have gotten stuck at a local maximum.
Setting tau^2 = 0. Check the profile likelihood plot with profile().
I cannot find something that explain how to explain me for Fisher algorithm or i am not so good to find something. The only think i know is the tau^=0 mean no heterogeneity so i can combine the datasets.
-
I use the same code with out covariates and the warning just disappear
so my question is, can i don’t use covariates ? -
can i produce forest plot based random effect model based in MMPHin tool?
so i can compare the different state of disease like paired-test
I am sorry for so match question, If anyone can help, it would be greatly appreciated!!!
Thanks for your support