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Runs checks for appropriate arguments before running emuFit()

Source: R/emuFit_check.R
emuFit_check.Rd

Runs checks for appropriate arguments before running emuFit()

Usage

emuFit_check(
  Y,
  X = NULL,
  formula = NULL,
  data = NULL,
  assay_name = NULL,
  cluster = NULL,
  B_null_list = NULL,
  test_kj = NULL,
  match_row_names = TRUE,
  verbose = FALSE,
  remove_zero_comparison_pvals = 0.01,
  unobserved_taxon_error = TRUE
)

Arguments

Y

an n x J matrix or dataframe of nonnegative observations, or a phyloseq object containing an otu table and sample data.

X

an n x p matrix or dataframe of covariates (optional)

formula

a one-sided formula specifying the form of the mean model to be fit

data

an n x p data frame containing variables given in formula

assay_name

a string containing the desired assay name within a TreeSummarizedExperiment object. This is only required if Y is a TreeSummarizedExperiment object, otherwise this argument does nothing and can be ignored.

cluster

a vector giving cluster membership for each row of Y to be used in computing GEE test statistics. Default is NULL, in which case rows of Y are treated as independent.

B_null_list

list of starting values of coefficient matrix (p x J) for null estimation. This should either be a list with the same length as test_kj. If you only want to provide starting values for some tests, include the other elements of the list as NULL.

test_kj

a data frame whose rows give coordinates (in category j and covariate k) of elements of B to construct hypothesis tests for. If test_kj is not provided, all elements of B save the intercept row will be tested.

match_row_names

logical: Make sure rows on covariate data and response data correspond to the same sample by comparing row names and subsetting/reordering if necessary.

verbose

provide updates as model is being fitted? Defaults to FALSE. If user sets verbose = TRUE, then key messages about algorithm progress will be displayed. If user sets verbose = "development", then key messages and technical messages about convergence will be displayed. Most users who want status updates should set verbose = TRUE.

remove_zero_comparison_pvals

Should score p-values be replaced with NA for zero-comparison parameters? These parameters occur for categorical covariates with three or more levels, and represent parameters that compare a covariate level to the reference level for a category in which the comparison level and reference level both have 0 counts in all samples. These parameters can have misleadingly small p-values and are not thought to have scientifically interesting signals. We recommend removing them before analyzing data further. If TRUE, all zero-comparison parameter p-values will be set to NA. If FALSE no zero-comparison parameter p-values will be set to NA. If a value between 0 and 1, all zero-comparison p-values below the value will be set to NA. Default is 0.01.

unobserved_taxon_error

logical: should an error be thrown if Y includes taxa that have 0 counts for all samples? Default is TRUE.

Value

returns objects Y, X, cluster, and B_null_list, which may be modified by tests, and throw any useful errors, warnings, or messages.