tsea_dup_hyperG: Target Set Enrichment Analysis (TSEA) with Hypergeometric...

In signatureSearch: Environment for Gene Expression Searching Combined with Functional Enrichment Analysis

Description

The tsea_dup_hyperG function performs Target Set Enrichment Analysis (TSEA) based on a modified hypergeometric test that supports test sets with duplications. This is achieved by maintaining the frequency information of duplicated items in form of weighting values.

Usage

tsea_dup_hyperG(
  drugs,
  universe = "Default",
  type = "GO",
  ont = "MF",
  pAdjustMethod = "BH",
  pvalueCutoff = 0.05,
  qvalueCutoff = 0.05,
  minGSSize = 5,
  maxGSSize = 500,
  dt_anno = "all",
  readable = FALSE
)

Arguments

drugs	character vector containing drug identifiers used for functional enrichment testing. This can be the top ranking drugs from a GESS result. Internally, drug test sets are translated to the corresponding target protein test sets based on the drug-target annotations provided under the dt_anno argument.
universe	character vector defining the universe of genes/proteins. If set as 'Default', it uses all genes/proteins present in the corresponding annotation system (e.g. GO, KEGG or Reactome). If 'type' is 'GO', it can be assigned a custom vector of gene SYMBOL IDs. If 'type' is 'KEGG' or 'Reactome', the vector needs to contain Entrez gene IDs.
type	one of 'GO', 'KEGG' or 'Reactome'
ont	character(1). If type is 'GO', assign ont (ontology) one of 'BP','MF', 'CC' or 'ALL'. If type is 'KEGG' or 'Reactome', ont is ignored.
pAdjustMethod	p-value adjustment method, one of 'holm', 'hochberg', 'hommel', 'bonferroni', 'BH', 'BY', 'fdr'
pvalueCutoff	double, p-value cutoff
qvalueCutoff	double, qvalue cutoff
minGSSize	integer, minimum size of each gene set in annotation system
maxGSSize	integer, maximum size of each gene set in annotation system
dt_anno	drug-target annotation source. Currently, one of 'DrugBank', 'CLUE', 'STITCH' or 'all'. If 'dt_anno' is 'all', the targets from the DrugBank, CLUE and STITCH databases will be combined. Usually, it is recommended to set the 'dt_anno' to 'all' since it provides the most complete drug-target annotations. Choosing a single annotation source results in sparser drug-target annotations (particularly CLUE), and thus less complete enrichment results.
readable	TRUE or FALSE, it applies when type is 'KEGG' or 'Reactome' indicating whether to convert gene Entrez ids to gene Symbols in the 'itemID' column in the result table.

Details

The classical hypergeometric test assumes uniqueness in its test sets. To maintain the duplication information in the test sets used for TSEA, the values of the total number of genes/proteins in the test set and the number of genes/proteins in the test set annotated at a functional category are adjusted by maintaining their frequency information in the test set rather than counting each entry only once. Removing duplications in TSEA would be inappropriate since it would erase one of the most important pieces of information of this approach.

Value

feaResult object, the result table contains the enriched functional categories (e.g. GO terms or KEGG pathways) ranked by the corresponding enrichment statistic.

Column description

The TSEA results (including tsea_dup_hyperG) stored in the feaResult object can be returned with the result method in tabular format, here tibble. The columns of this tibble are described below.

• GeneRatio: ratio of genes in the test set that are annotated at a specific GO node or KEGG pathway

• BgRatio: ratio of background genes that are annotated at a specific GO node or KEGG pathway

• pvalue: raw p-value of enrichment test

Additional columns are described under the 'result' slot of the feaResult object.

See Also

feaResult, fea

Examples

data(drugs10)
## GO annotation system
# res1 <- tsea_dup_hyperG(drugs=drugs10, universe="Default", 
#                         type="GO", ont="MF", pvalueCutoff=0.05,
#                         pAdjustMethod="BH", qvalueCutoff=0.1, 
#                         minGSSize=5, maxGSSize=500)
# result(res1)
#
## KEGG annotation system
# res2 <- tsea_dup_hyperG(drugs=drugs10, type="KEGG", 
#                         pvalueCutoff=0.1, qvalueCutoff=0.2, 
#                         minGSSize=10, maxGSSize=500)
#
## Reactome annotation system
# res3 <- tsea_dup_hyperG(drugs=drugs10, type="Reactome", 
#                         pvalueCutoff=1, qvalueCutoff=1)

signatureSearch documentation built on April 16, 2021, 6 p.m.