regression | R Documentation |
Run regression models with adjusting for covariates. 'regression_each' is used for one outcome. In 'regression', several outcomes can be specified to run together.
regression(
object,
phenoData = NULL,
model = NULL,
outcome = NULL,
covars = NULL,
factors = NULL,
feature_name = NULL,
time = NULL,
verbose = TRUE,
ncpus = 1,
p.adjust.method = "bonferroni",
...
)
regression_each(
object,
phenoData = NULL,
model = NULL,
formula = NULL,
outcome = NULL,
covars = NULL,
factors = NULL,
feature_name = NULL,
time = NULL,
verbose = TRUE,
ncpus = 1,
p.adjust.method = "bonferroni",
...
)
regression_each_as_outcome(
object,
phenoData = NULL,
exposure = NULL,
covars = NULL,
factors = NULL,
feature_name = NULL,
verbose = TRUE,
ncpus = 1,
p.adjust.method = "bonferroni",
...
)
object |
A Metabolite object. |
phenoData |
A data.table with outcome and covariates. If 'phenoData' is NULL, '@sampleData' will be used. |
model |
Specify a regression model. See |
outcome |
Column name of the outcome variable. |
covars |
Column names of covariates. |
factors |
Variables to be treated as factor. |
feature_name |
A vector of selected metabolites to run. If both feature_name and random_select are NULL, will run regression for all features. |
time |
Column name of survival time, used in cox regression, see |
verbose |
Print log information. |
ncpus |
Number of CPUS for parallele job. |
p.adjust.method |
Adjust for P value method, see |
... |
Further arguments passed to regression model. |
formula |
A character or formula object to fit model (only used in 'regression_each') |
exposure |
exposure variables. |
term estimate std.error statistic p.value n outcome p.value.adj.
regression_each_as_outcome
: Run linear regression models where each feature is outcome.
data(df_plasma)
fit_lm <- regression(object = df_plasma, phenoData = NULL, model = "lm",
outcome = "BMI", covars = c("AGE", "GENDER", "ETHNICITY"), factors = "ETHNICITY")
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