Description Usage Arguments Value Examples
This function does meta-analysis based on estimates and standard errors from taxa/pathway abundance comparison using random effect and fixed effect meta-analysis models.
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taxcomdat |
matrice of estimates and SE of all taxa/pathways combined from all included studies. |
estimate.pattern |
string pattern for estimates. Default is "Estimate.". |
se.pattern |
string pattern for standard error. Default is "Std. Error.". |
summary.measure |
"RR" for estimates from GAMLSS with BEZI family and "RD" for estimates from Linear/linear mixed effect model. Default is "RR" |
pool.var |
name of id variable for meta-analysis. Default is "id". |
studylab |
name of variable characterizing included studies. Default is "study". |
backtransform |
whether or not to perform backtransformation of the estimates. Default is FALSE. |
percent.meta |
the threshold percentage of number of studies that a taxa is available to do meta-analysis. Default is 0.5 |
p.adjust.method |
method for multiple testing adjustment (available methods of the function p.adjust). Default is "fdr". |
a list of matrices of results for all variables in the comparison models.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # load saved GAMLSS-BEZI results of four studies
# for the comparison of bacterial taxa relative abundance between
# genders adjusted for breastfeeding and infant age at sample collection
data(tabsex4)
#select only taxonomies of a small phylum for meta-analysis example
# (to save running time)
tlm<-tabsex4$id[grep("k__bacteria.p__fusobacteria",tabsex4$id)]
# meta-analysis
metab.sex<-meta.taxa(taxcomdat=tabsex4[tabsex4$id %in% tlm,],
summary.measure="RR", pool.var="id", studylab="study",
backtransform=FALSE, percent.meta=0.5, p.adjust.method="fdr")
#show results by table and plot
#phylum
#table
metatab.show(metatab=metab.sex$random,com.pooled.tab=tabsex4[tabsex4$id %in% tlm,],
tax.lev="l2",showvar="genderMale",p.cutoff.type="p", p.cutoff=1,display="table")
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