View source: R/allSorenThreshold.R
allSorenThreshold | R Documentation |
sorenThreshold
along the specified GO ontologies and GO levelsIterate sorenThreshold
along the specified GO ontologies and GO levels
allSorenThreshold(x, ...)
## S3 method for class 'list'
allSorenThreshold(
x,
geneUniverse,
orgPackg,
boot = FALSE,
nboot = 10000,
boot.seed = 6551,
ontos = c("BP", "CC", "MF"),
GOLevels = seq.int(3, 10),
trace = TRUE,
alpha = 0.05,
precis = 0.001,
...
)
## S3 method for class 'allTableList'
allSorenThreshold(
x,
boot = FALSE,
nboot = 10000,
boot.seed = 6551,
ontos,
GOLevels,
trace = TRUE,
alpha = 0.05,
precis = 0.001,
...
)
x |
either an object of class "list" or an object of class "allTableList". In the first case, each of idata:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABIAAAASCAYAAABWzo5XAAAAWElEQVR42mNgGPTAxsZmJsVqQApgmGw1yApwKcQiT7phRBuCzzCSDSHGMKINIeDNmWQlA2IigKJwIssQkHdINgxfmBBtGDEBS3KCxBc7pMQgMYE5c/AXPwAwSX4lV3pTWwAAAABJRU5ErkJggg==ts elements must be a "character" vector of gene identifiers. In the second case, the object corresponds to all contingency tables of joint enrichment along one or more GO ontologies and one or more GO levels. |
... |
extra parameters for function |
geneUniverse |
character vector containing all genes from where geneLists have been extracted |
orgPackg |
a string with the name of the annotation package |
boot |
boolean. If TRUE, the confidence intervals and the test p-values are computed by means of a bootstrap approach instead of the asymptotic normal approach. Defaults to FALSE. |
nboot |
numeric, number of initially planned bootstrap replicates. Ignored if
|
boot.seed |
starting random seed for all bootstrap iterations. Defaults to 6551. see the details section |
ontos |
"character", GO ontologies to analyse. |
GOLevels |
"integer", GO levels to analyse inside each one of these GO ontologies. |
trace |
Logical. If TRUE (default), the (usually very time consuming) process is traced along the specified GO ontologies and levels. |
alpha |
simultaneous nominal significance level for the equivalence tests to be repeteadly performed, defaults to 0.05 |
precis |
numerical precision in the iterative search of the equivalence threshold dissimilarities, |
An object of class "distList". It is a list with as many components as GO ontologies have been analysed. Each of these elements is itself a list with as many components as GO levels have been analysed. Finally, the elements of these lists are objects of class "dist" with the Sorensen-Dice equivalence threshold dissimilarity.
allSorenThreshold(list)
: S3 method for class "list"
allSorenThreshold(allTableList)
: S3 method for class "allTableList"
# # This example is extremely time consuming, it scans two GO ontologies and three
# # GO levels inside them to perform the equivalence test.
# # Gene universe:
# data("humanEntrezIDs")
# # Gene lists to be explored for enrichment:
# data("allOncoGeneLists")
# allSorenThreshold(allOncoGeneLists,
# geneUniverse = humanEntrezIDs, orgPackg = "org.Hs.eg.db",
#
# Much faster:
# Object \code{allTabs} of class "allTableList" contains all the pairwise contingency tables of
# joint enrichment for the gene lists in \code{allOncoGeneLists}, obtained along all three GO
# ontologies and along GO levels 3 to 10:
data(allTabs)
dSors <- allSorenThreshold(allTabs, ontos = c("MF", "BP"), GOLevels = seq.int(4,6))
dSors$BP$`level 5`
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