hima2 | R Documentation |
hima2
is an upgraded version of hima for estimating and testing high-dimensional mediation effects.
hima2(
formula,
data.pheno,
data.M,
outcome.family = c("gaussian", "binomial", "survival", "quantile"),
mediator.family = c("gaussian", "negbin", "compositional"),
penalty = c("DBlasso", "MCP", "SCAD", "lasso"),
topN = NULL,
scale = TRUE,
verbose = FALSE,
...
)
formula |
an object of class |
data.pheno |
a data frame containing exposure and covariates that are listed in the right hand side of the |
data.M |
a |
outcome.family |
either |
mediator.family |
either |
penalty |
the penalty to be applied to the model. Either |
topN |
an integer specifying the number of top markers from sure independent screening.
Default = |
scale |
logical. Should the function scale the data (exposure, mediators, and covariates)? Default = |
verbose |
logical. Should the function be verbose and shows the progression? Default = |
... |
other arguments. |
A data.frame containing mediation testing results of selected mediators.
1. Zhang H, Zheng Y, Zhang Z, Gao T, Joyce B, Yoon G, Zhang W, Schwartz J, Just A, Colicino E, Vokonas P, Zhao L, Lv J, Baccarelli A, Hou L, Liu L. Estimating and Testing High-dimensional Mediation Effects in Epigenetic Studies. Bioinformatics. 2016. DOI: 10.1093/bioinformatics/btw351. PMID: 27357171; PMCID: PMC5048064
2. Zhang H, Zheng Y, Hou L, Zheng C, Liu L. Mediation Analysis for Survival Data with High-Dimensional Mediators. Bioinformatics. 2021. DOI: 10.1093/bioinformatics/btab564. PMID: 34343267; PMCID: PMC8570823
3. Zhang H, Chen J, Feng Y, Wang C, Li H, Liu L. Mediation effect selection in high-dimensional and compositional microbiome data. Stat Med. 2021. DOI: 10.1002/sim.8808. PMID: 33205470; PMCID: PMC7855955
4. Zhang H, Chen J, Li Z, Liu L. Testing for mediation effect with application to human microbiome data. Stat Biosci. 2021. DOI: 10.1007/s12561-019-09253-3. PMID: 34093887; PMCID: PMC8177450
5. Perera C, Zhang H, Zheng Y, Hou L, Qu A, Zheng C, Xie K, Liu L. HIMA2: high-dimensional mediation analysis and its application in epigenome-wide DNA methylation data. BMC Bioinformatics. 2022. DOI: 10.1186/s12859-022-04748-1. PMID: 35879655; PMCID: PMC9310002
6. Zhang H, Hong X, Zheng Y, Hou L, Zheng C, Wang X, Liu L. High-Dimensional Quantile Mediation Analysis with Application to a Birth Cohort Study of Mother–Newborn Pairs. Bioinformatics. 2024. DOI: 10.1093/bioinformatics/btae055. PMID: 38290773; PMCID: PMC10873903
## Not run:
# Note: In the following examples, M1, M2, and M3 are true mediators.
data(himaDat)
# Example 1 (continous outcome):
head(himaDat$Example1$PhenoData)
e1 <- hima2(Outcome ~ Treatment + Sex + Age,
data.pheno = himaDat$Example1$PhenoData,
data.M = himaDat$Example1$Mediator,
outcome.family = "gaussian",
mediator.family = "gaussian",
penalty = "DBlasso",
scale = FALSE) # Disabled only for example data
e1
attributes(e1)$variable.labels
# Example 2 (binary outcome):
head(himaDat$Example2$PhenoData)
e2 <- hima2(Disease ~ Treatment + Sex + Age,
data.pheno = himaDat$Example2$PhenoData,
data.M = himaDat$Example2$Mediator,
outcome.family = "binomial",
mediator.family = "gaussian",
penalty = "DBlasso",
scale = FALSE) # Disabled only for example data
e2
attributes(e2)$variable.labels
# Example 3 (time-to-event outcome):
head(himaDat$Example3$PhenoData)
e3 <- hima2(Surv(Status, Time) ~ Treatment + Sex + Age,
data.pheno = himaDat$Example3$PhenoData,
data.M = himaDat$Example3$Mediator,
outcome.family = "survival",
mediator.family = "gaussian",
penalty = "DBlasso",
scale = FALSE) # Disabled only for example data
e3
attributes(e3)$variable.labels
# Example 4 (compositional data as mediator, e.g., microbiome):
head(himaDat$Example4$PhenoData)
e4 <- hima2(Outcome ~ Treatment + Sex + Age,
data.pheno = himaDat$Example4$PhenoData,
data.M = himaDat$Example4$Mediator,
outcome.family = "gaussian",
mediator.family = "compositional",
penalty = "DBlasso",
scale = FALSE) # Disabled only for example data
e4
attributes(e4)$variable.labels
#' # Example 5 (quantile mediation anlaysis):
head(himaDat$Example5$PhenoData)
# Note that the function will prompt input for quantile level.
e5 <- hima2(Outcome ~ Treatment + Sex + Age,
data.pheno = himaDat$Example5$PhenoData,
data.M = himaDat$Example5$Mediator,
outcome.family = "quantile",
mediator.family = "gaussian",
penalty = "MCP", # Quantile HIMA does not support DBlasso
scale = FALSE, # Disabled only for example data
tau = c(0.3, 0.5, 0.7)) # Specify multiple quantile level
e5
attributes(e5)$variable.labels
## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.