sysCorGenes: sysUpCorGenes.

In hyginn/BCB420.2019.ESA: Exploratory Systems Analysis Tools

Description

sysUpCorGenes Finding pairs of genes that their expression profiles are the most positively or negatively correlated.

Usage

sysCorGenes(exProfS, nUpMost = FALSE, direction = "Positive",
  multipleTests = "Bonferroni", alpha = 0.05)

Arguments

exProfS	(numeric) A matrix of expression profiles, with column dimensions equal to the number of microarray experiments, and row dimensions that are equal to the number of queried genes. All genes must have information for all experiments (i.e., no NAs are allowed). The matrix can be produced by the helper function sysExProf().
nUpMost	(numeric|logical) Either FALSE or a numeric vector of 1L length. FALSE returns all significantly correlated genes. A numeric vector sets the number of most highly correlated pairs of genes to return by the function. The default is FALSE.
direction	(character) A vector of 1L length of either "Positive" or "Negative". "Positive" returns pairs of genes that are significantly positively correlated. "Negative" returns pairs of genes that are significantly negatively correlated. The default is set to "Positive".
multipleTests	(character) A vector of 1L length of either "Bonferroni" or "BH" (Benjamini-Hochberg). Sets the multiple tests correction approach. The default is "Bonferroni".
alpha	(numeric) A vector of 1L length. Sets the value of alpha for deciding the cutoff for significant results. The Default is 0.05.

Value

(character) A vector of unique genes (HGNC symbols) that were found to be significantly correlated, according to the conditions set by the parameters. For a numeric value of nUpMost, although the number of pairs of genes was set, the number of the returned genes is not always equal to 2 * "nUpMost", because some of the pairs may contain the same genes, while the function returns only a vector of unique genes.

Details

A helper function that produces a character vector of unique genes (HGNC symbols) that belongs to pairs of genes that their expression profiles were shown to be either positively or negatively correlated. It is also possible to specify the number the of most highly negatively or positively correlated pairs of genes to retrieve.

Author(s)

Sapir Labes (aut)

See Also

cor.test Test for association between paired samples, using one of Pearson's product moment correlation coefficient, Kendall's tau or Spearman's rho.

Examples

## Not run: 
# Vector of the 12 up most positively correlated pairs of genes of "SLIGR"
# system.
# mySymbols <- SyDBgetSysSymbols(fetchData("SysDB"),"SLIGR")[[1]]
# exProfS <- matrix(data = sample(1:200, 4 * length(mySymbols), replace = TRUE),
#                  ncol = 4) #generating synthetic expression data
# row.names(exProfS) <- mySymbols
# sysUpCorGenes(exProfS = exProfS, nUpMost = 12)

## End(Not run)

hyginn/BCB420.2019.ESA documentation built on May 29, 2019, 1:23 p.m.