dot-permTestDiffAsso: Permutation Tests for Determining Differential Associations

In stefpeschel/NetCoMi: Network Construction and Comparison for Microbiome Data

Permutation Tests for Determining Differential Associations

Description

The function implements procedures to test whether pairs of taxa are differentially associated, whether a taxon is differentially associated to all other taxa, or whether two networks are differentially associated between two groups as proposed by Gill et al.(2010).

Usage

.permTestDiffAsso(
  countMat1,
  countMat2,
  countsJoint,
  normCounts1,
  normCounts2,
  assoMat1,
  assoMat2,
  paramsNetConstruct,
  method = c("connect.pairs", "connect.variables", "connect.network"),
  fisherTrans = TRUE,
  pvalsMethod = "pseudo",
  adjust = "lfdr",
  adjust2 = "holm",
  trueNullMethod = "convest",
  alpha = 0.05,
  lfdrThresh = 0.2,
  nPerm = 1000,
  matchDesign = NULL,
  callNetConstr = NULL,
  cores = 4,
  verbose = TRUE,
  logFile = "log.txt",
  seed = NULL,
  fileLoadAssoPerm = NULL,
  fileLoadCountsPerm = NULL,
  storeAssoPerm = FALSE,
  fileStoreAssoPerm = "assoPerm",
  storeCountsPerm = FALSE,
  fileStoreCountsPerm = c("countsPerm1", "countsPerm2"),
  assoPerm = NULL
)

Arguments

countMat1, countMat2	matrices containing microbiome data (read counts) of group 1 and group 2 (rows represent samples and columns taxonomic units, respectively).
countsJoint	joint count matrices before preprocessing
normCounts1, normCounts2	normalized count matrices.
assoMat1, assoMat2	association matrices corresponding to the two count matrices. The associations must have been estimated from the count matrices countMat1 and countMat2.
paramsNetConstruct	parameters used for network construction.
method	character vector indicating the tests to be performed. Possible values are "connect.pairs" (differentially correlated taxa pairs), "connect.variables" (one taxon to all other) and "connect.network" (differentially connected networks). By default, all three tests are conducted.
fisherTrans	logical indicating whether the correlation values should be Fisher-transformed.
pvalsMethod	currently only "pseudo" is available, where 1 is added to the number of permutations and the permutation test statistics being more extreme than the observed one in order to avoid zero p-values.
adjust	multiple testing adjustment for the tests for differentially correlated pairs of taxa; possible values are "lfdr" (default) for local false discovery rate correction (via fdrtool) or one of the methods provided by p.adjust
adjust2	multiple testing adjustment for the tests if a taxa pair is differentially correlated to all other taxa; possible methods are those provided by p.adjust (a few hundred tests are necessary for the local fdr correction)
trueNullMethod	character indicating the method used for estimating the proportion of true null hypotheses from a vector of p-values. Used for the adaptive Benjamini-Hochberg method for multiple testing adjustment (chosen by adjust = "adaptBH").
alpha	significance level
lfdrThresh	defines a threshold for the local fdr if "lfdr" is chosen as method for multiple testing correction; defaults to 0.2, which means that correlations with a corresponding local fdr less than or equal to 0.2 are identified as significant
nPerm	number of permutations
matchDesign	Numeric vector with two elements specifying an optional matched-group (i.e. matched-pair) design, which is used for the permutation tests in netCompare and diffnet. c(1,1) corresponds to a matched-pair design. A 1:2 matching, for instance, is defined by c(1,2), which means that the first sample of group 1 is matched to the first two samples of group 2 and so on. The appropriate order of samples must be ensured. If NULL, the group memberships are shuffled randomly while group sizes identical to the original data set are ensured.
callNetConstr	call inherited from netConstruct().
cores	number of CPU cores (permutation tests are executed parallel)
verbose	if TRUE, status messages and numbers of SparCC iterations are printed
logFile	character string naming the log file within which the current iteration number is stored
seed	an optional seed for reproducibility of the results
fileLoadAssoPerm	character giving the name (without extenstion) or path of the file storing the "permuted" association/dissimilarity matrices that have been exported by setting storeAssoPerm to TRUE. Only used for permutation tests. Set to NULL if no existing associations should be used.
fileLoadCountsPerm	character giving the name (without extenstion) or path of the file storing the "permuted" count matrices that have been exported by setting storeCountsPerm to TRUE. Only used for permutation tests, and if fileLoadAssoPerm = NULL. Set to NULL if no existing count matrices should be used.
storeAssoPerm	logical indicating whether the association (or dissimilarity) matrices for the permuted data should be stored in a file. The filename is given via fileStoreAssoPerm. If TRUE, the computed "permutation" association/dissimilarity matrices can be reused via fileLoadAssoPerm to save runtime. Defaults to FALSE.
fileStoreAssoPerm	character giving the file name to store a matrix containing a matrix with associations/dissimilarities for the permuted data. Can also be a path.
storeCountsPerm	logical indicating whether the permuted count matrices should be stored in an external file. Defaults to FALSE.
fileStoreCountsPerm	character vector with two elements giving the names of two files storing the permuted count matrices belonging to the two groups.
assoPerm	not used anymore.

References

\insertRef

gill2010statisticalNetCoMi

\insertRefknijnenburg2009fewerNetCoMi

See Also

diffnet

stefpeschel/NetCoMi documentation built on Feb. 4, 2024, 8:20 a.m.