bioconductor v3.9.0 DOSE
This package implements five methods proposed by
Link to this section Summary
Functions
Disease Ontology Semantic and Enrichment analysis Implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for measuring DO semantic similarities, and hypergeometric test for enrichment analysis.
Datasets
EXTID2NAME
GSEA_internal
clusterSim
compute information content
doSim
Enrichment analysis based on the DisGeNET ( http://www.disgenet.org/ )
enrichDGN
DO Enrichment Analysis
enrichNCG
Class "enrichResult" This class represents the result of enrichment analysis.
enrich.internal
fortify
convert Gene ID to DO Terms
geneID generic
geneInCategory generic
geneSim
DisGeNET Gene Set Enrichment Analysis
DO Gene Set Enrichment Analysis
NCG Gene Set Enrichment Analysis
Class "gseaResult" This class represents the result of GSEA analysis
gsfilter
mclusterSim
parse_ratio
rebuiding annotation data
Objects exported from other packages
setReadable
show method
simplot
summary method
theme_dose
Link to this section Functions
DOSE_package()
Disease Ontology Semantic and Enrichment analysis Implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for measuring DO semantic similarities, and hypergeometric test for enrichment analysis.
Description
This package is designed to estimate DO-based semantic similarity measurement and enrichment analysis.
Details
list(list("ll"), list(" Package: ", list(), " DOSE", list(), " Type: ", list(), " Package", list(), " Version: ", list(), " ", "2.3.5", list(), " Date: ", list(), " 2-27-2012", list(), " biocViews:", list(), " Bioinformatics, ", "Annotation", list(), " Depends:", list(), " ", list(), " Imports: ", list(), " methods, AnnotationDbi, ", "DO.db", list(), " Suggests:", list(), " clusterProfiler, GOSemSim", list(), " License: ", list(), " ", "Artistic-2.0", list(), " "))
Seealso
enrichResult
Author
Guangchuang Yu, Li-Gen Wang
Maintainer: Guangchuang Yu guangchuangyu@gmail.com
DataSet()
Datasets
Description
Information content and DO term to entrez gene IDs mapping
EXTID2NAME()
EXTID2NAME
Description
mapping gene ID to gene Symbol
Usage
EXTID2NAME(OrgDb, geneID, keytype)Arguments
| Argument | Description |
|---|---|
OrgDb | OrgDb |
geneID | entrez gene ID |
keytype | keytype |
Value
gene symbol
Author
Guangchuang Yu http://guangchuangyu.github.io
GSEA_internal()
GSEA_internal
Description
generic function for gene set enrichment analysis
Usage
GSEA_internal(geneList, exponent, nPerm, minGSSize, maxGSSize,
pvalueCutoff, pAdjustMethod, verbose, seed = FALSE, USER_DATA,
by = "fgsea")Arguments
| Argument | Description |
|---|---|
geneList | order ranked geneList |
exponent | weight of each step |
nPerm | permutation numbers |
minGSSize | minimal size of each geneSet for analyzing |
maxGSSize | maximal size of each geneSet for analyzing |
pvalueCutoff | p value Cutoff |
pAdjustMethod | p value adjustment method |
verbose | print message or not |
seed | set seed inside the function to make result reproducible. FALSE by default. |
USER_DATA | annotation data |
by | one of 'fgsea' or 'DOSE' |
Value
gseaResult object
Author
Yu Guangchuang
clusterSim()
clusterSim
Description
semantic similarity between two gene clusters
Usage
clusterSim(cluster1, cluster2, measure = "Wang", combine = "BMA")Arguments
| Argument | Description |
|---|---|
cluster1 | a vector of gene IDs |
cluster2 | another vector of gene IDs |
measure | One of "Resnik", "Lin", "Rel", "Jiang" and "Wang" methods. |
combine | One of "max", "avg", "rcmax", "BMA" methods, for combining |
Details
given two gene clusters, this function calculates semantic similarity between them.
Value
similarity
Author
Yu Guangchuang
Examples
cluster1 <- c("835", "5261","241", "994")
cluster2 <- c("307", "308", "317", "321", "506", "540", "378", "388", "396")
clusterSim(cluster1, cluster2)computeIC()
compute information content
Description
compute information content
Usage
computeIC(ont = "DO", organism = "human")Arguments
| Argument | Description |
|---|---|
ont | "DO" |
organism | "human" |
Author
Guangchuang Yu http://guangchuangyu.github.io
doSim()
doSim
Description
measuring similarities between two DO term vectors.
Usage
doSim(DOID1, DOID2, measure = "Wang")Arguments
| Argument | Description |
|---|---|
DOID1 | DO term vector |
DOID2 | DO term vector |
measure | one of "Wang", "Resnik", "Rel", "Jiang", and "Lin". |
Details
provide two DO term vectors, this function will calculate their similarities.
Value
score matrix
Author
Guangchuang Yu https://guangchuangyu.github.io
enrichDGN()
Enrichment analysis based on the DisGeNET ( http://www.disgenet.org/ )
Description
given a vector of genes, this function will return the enrichment NCG categories with FDR control
Usage
enrichDGN(gene, pvalueCutoff = 0.05, pAdjustMethod = "BH", universe,
minGSSize = 10, maxGSSize = 500, qvalueCutoff = 0.2,
readable = FALSE)Arguments
| Argument | Description |
|---|---|
gene | a vector of entrez gene id |
pvalueCutoff | pvalue cutoff |
pAdjustMethod | one of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none" |
universe | background genes |
minGSSize | minimal size of genes annotated by NCG category for testing |
maxGSSize | maximal size of each geneSet for analyzing |
qvalueCutoff | qvalue cutoff |
readable | whether mapping gene ID to gene Name |
Value
A enrichResult instance
Author
Guangchuang Yu
References
Janet et al. (2015) DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes. Database bav028 http://database.oxfordjournals.org/content/2015/bav028.long
enrichDGNv()
enrichDGN
Description
Enrichment analysis based on the DisGeNET ( http://www.disgenet.org/ )
Usage
enrichDGNv(snp, pvalueCutoff = 0.05, pAdjustMethod = "BH", universe,
minGSSize = 10, maxGSSize = 500, qvalueCutoff = 0.2,
readable = FALSE)Arguments
| Argument | Description |
|---|---|
snp | a vector of SNP |
pvalueCutoff | pvalue cutoff |
pAdjustMethod | one of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none" |
universe | background genes |
minGSSize | minimal size of genes annotated by NCG category for testing |
maxGSSize | maximal size of each geneSet for analyzing |
qvalueCutoff | qvalue cutoff |
readable | whether mapping gene ID to gene Name |
Details
given a vector of genes, this function will return the enrichment NCG categories with FDR control
Value
A enrichResult instance
Author
Guangchuang Yu
References
Janet et al. (2015) DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes. Database bav028 http://database.oxfordjournals.org/content/2015/bav028.long
enrichDO()
DO Enrichment Analysis
Description
Given a vector of genes, this function will return the enrichment DO categories with FDR control.
Usage
enrichDO(gene, ont = "DO", pvalueCutoff = 0.05, pAdjustMethod = "BH",
universe, minGSSize = 10, maxGSSize = 500, qvalueCutoff = 0.2,
readable = FALSE)Arguments
| Argument | Description |
|---|---|
gene | a vector of entrez gene id |
ont | one of DO or DOLite. |
pvalueCutoff | pvalue cutoff |
pAdjustMethod | one of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none" |
universe | background genes |
minGSSize | minimal size of genes annotated by NCG category for testing |
maxGSSize | maximal size of each geneSet for analyzing |
qvalueCutoff | qvalue cutoff |
readable | whether mapping gene ID to gene Name |
Value
A enrichResult instance.
Seealso
Author
Guangchuang Yu http://guangchuangyu.github.io
Examples
data(geneList)
gene = names(geneList)[geneList > 1]
yy = enrichDO(gene, pvalueCutoff=0.05)
summary(yy)enrichNCG()
enrichNCG
Description
Enrichment analysis based on the Network of Cancer Genes database (http://ncg.kcl.ac.uk/)
Usage
enrichNCG(gene, pvalueCutoff = 0.05, pAdjustMethod = "BH", universe,
minGSSize = 10, maxGSSize = 500, qvalueCutoff = 0.2,
readable = FALSE)Arguments
| Argument | Description |
|---|---|
gene | a vector of entrez gene id |
pvalueCutoff | pvalue cutoff |
pAdjustMethod | one of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none" |
universe | background genes |
minGSSize | minimal size of genes annotated by NCG category for testing |
maxGSSize | maximal size of each geneSet for analyzing |
qvalueCutoff | qvalue cutoff |
readable | whether mapping gene ID to gene Name |
Details
given a vector of genes, this function will return the enrichment NCG categories with FDR control
Value
A enrichResult instance
Author
Guangchuang Yu
enrichResult_class()
Class "enrichResult" This class represents the result of enrichment analysis.
Description
Class "enrichResult" This class represents the result of enrichment analysis.
Seealso
Author
Guangchuang Yu https://guangchuangyu.github.io
enricher_internal()
enrich.internal
Description
interal method for enrichment analysis
Usage
enricher_internal(gene, pvalueCutoff, pAdjustMethod = "BH",
universe = NULL, minGSSize = 10, maxGSSize = 500,
qvalueCutoff = 0.2, USER_DATA)Arguments
| Argument | Description |
|---|---|
gene | a vector of entrez gene id. |
pvalueCutoff | Cutoff value of pvalue. |
pAdjustMethod | one of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none" |
universe | background genes |
minGSSize | minimal size of genes annotated by Ontology term for testing. |
maxGSSize | maximal size of each geneSet for analyzing |
qvalueCutoff | cutoff of qvalue |
USER_DATA | ontology information |
Details
using the hypergeometric model
Value
A enrichResult instance.
Author
Guangchuang Yu http://guangchuangyu.github.io
fortifyenrichResult()
fortify
Description
convert enrichResult object for ggplot2
Usage
list(list("fortify"), list("enrichResult"))(model, data, showCategory = 5,
by = "Count", order = FALSE, drop = FALSE, split = NULL, ...)Arguments
| Argument | Description |
|---|---|
model | enrichResult object |
data | not use here |
showCategory | Category numbers to show |
by | one of Count and GeneRatio |
order | logical |
drop | logical |
split | separate result by 'split' variable |
... | additional parameter |
gene2DO()
convert Gene ID to DO Terms
Description
provide gene ID, this function will convert to the corresponding DO Terms
Usage
gene2DO(gene)Arguments
| Argument | Description |
|---|---|
gene | entrez gene ID |
Value
DO Terms
Author
Guangchuang Yu http://guangchuangyu.github.io
geneID()
geneID generic
Description
geneID generic
Usage
geneID(x)Arguments
| Argument | Description |
|---|---|
x | enrichResult object |
Value
'geneID' return the 'geneID' column of the enriched result which can be converted to data.frame via 'as.data.frame'
Examples
data(geneList, package="DOSE")
de <- names(geneList)[1:100]
x <- enrichDO(de)
geneID(x)geneInCategory()
geneInCategory generic
Description
geneInCategory generic
Usage
geneInCategory(x)Arguments
| Argument | Description |
|---|---|
x | enrichResult |
Value
'geneInCategory' return a list of genes, by spliting the input gene vector to enriched functional categories
Examples
data(geneList, package="DOSE")
de <- names(geneList)[1:100]
x <- enrichDO(de)
geneInCategory(x)geneSim()
geneSim
Description
measuring similarities bewteen two gene vectors.
Usage
geneSim(geneID1, geneID2 = NULL, measure = "Wang", combine = "BMA")Arguments
| Argument | Description |
|---|---|
geneID1 | entrez gene vector |
geneID2 | entrez gene vector |
measure | one of "Wang", "Resnik", "Rel", "Jiang", and "Lin". |
combine | One of "max", "avg", "rcmax", "BMA" methods, for combining semantic similarity scores of multiple DO terms associated with gene/protein. |
Details
provide two entrez gene vectors, this function will calculate their similarity.
Value
score matrix
Author
Guangchuang Yu http://ygc.name
gseDGN()
DisGeNET Gene Set Enrichment Analysis
Description
perform gsea analysis
Usage
gseDGN(geneList, exponent = 1, nPerm = 1000, minGSSize = 10,
maxGSSize = 500, pvalueCutoff = 0.05, pAdjustMethod = "BH",
verbose = TRUE, seed = FALSE, by = "fgsea")Arguments
| Argument | Description |
|---|---|
geneList | order ranked geneList |
exponent | weight of each step |
nPerm | permutation numbers |
minGSSize | minimal size of each geneSet for analyzing |
maxGSSize | maximal size of each geneSet for analyzing |
pvalueCutoff | pvalue Cutoff |
pAdjustMethod | p value adjustment method |
verbose | print message or not |
seed | logical |
by | one of 'fgsea' or 'DOSE' |
Value
gseaResult object
Author
Yu Guangchuang
gseDO()
DO Gene Set Enrichment Analysis
Description
perform gsea analysis
Usage
gseDO(geneList, exponent = 1, nPerm = 1000, minGSSize = 10,
maxGSSize = 500, pvalueCutoff = 0.05, pAdjustMethod = "BH",
verbose = TRUE, seed = FALSE, by = "fgsea")Arguments
| Argument | Description |
|---|---|
geneList | order ranked geneList |
exponent | weight of each step |
nPerm | permutation numbers |
minGSSize | minimal size of each geneSet for analyzing |
maxGSSize | maximal size of each geneSet for analyzing |
pvalueCutoff | pvalue Cutoff |
pAdjustMethod | p value adjustment method |
verbose | print message or not |
seed | logical |
by | one of 'fgsea' or 'DOSE' |
Value
gseaResult object
Author
Yu Guangchuang
gseNCG()
NCG Gene Set Enrichment Analysis
Description
perform gsea analysis
Usage
gseNCG(geneList, exponent = 1, nPerm = 1000, minGSSize = 10,
maxGSSize = 500, pvalueCutoff = 0.05, pAdjustMethod = "BH",
verbose = TRUE, seed = FALSE, by = "fgsea")Arguments
| Argument | Description |
|---|---|
geneList | order ranked geneList |
exponent | weight of each step |
nPerm | permutation numbers |
minGSSize | minimal size of each geneSet for analyzing |
maxGSSize | maximal size of each geneSet for analyzing |
pvalueCutoff | pvalue Cutoff |
pAdjustMethod | p value adjustment method |
verbose | print message or not |
seed | logical |
by | one of 'fgsea' or 'DOSE' |
Value
gseaResult object
Author
Yu Guangchuang
gseaResult_class()
Class "gseaResult" This class represents the result of GSEA analysis
Description
Class "gseaResult" This class represents the result of GSEA analysis
Author
Guangchuang Yu https://guangchuangyu.github.io
gsfilter()
gsfilter
Description
filter enriched result by gene set size or gene count
Usage
gsfilter(x, by = "GSSize", min = NA, max = NA)Arguments
| Argument | Description |
|---|---|
x | instance of enrichResult or compareClusterResult |
by | one of 'GSSize' or 'Count' |
min | minimal size |
max | maximal size |
Value
update object
Author
Guangchuang Yu
mclusterSim()
mclusterSim
Description
Pairwise semantic similarity for a list of gene clusters
Usage
mclusterSim(clusters, measure = "Wang", combine = "BMA")Arguments
| Argument | Description |
|---|---|
clusters | A list of gene clusters |
measure | one of "Wang", "Resnik", "Rel", "Jiang", and "Lin". |
combine | One of "max", "avg", "rcmax", "BMA" methods, for combining semantic similarity scores of multiple DO terms associated with gene/protein. |
Value
similarity matrix
Author
Yu Guangchuang
Examples
cluster1 <- c("835", "5261","241")
cluster2 <- c("578","582")
cluster3 <- c("307", "308", "317")
clusters <- list(a=cluster1, b=cluster2, c=cluster3)
mclusterSim(clusters, measure="Wang")parse_ratio()
parse_ratio
Description
parse character ratio to double value, such as 1/5 to 0.2
Usage
parse_ratio(ratio)Arguments
| Argument | Description |
|---|---|
ratio | character vector of ratio to parse |
Value
A numeric vector (double) of parsed ratio
Author
Guangchuang Yu
rebuildAnnoData()
rebuiding annotation data
Description
rebuilding entrez and DO mapping datasets
Usage
rebuildAnnoData(file)Arguments
| Argument | Description |
|---|---|
file | do_rif.human.txt |
Author
Guangchuang Yu http://guangchuangyu.github.io
reexports()
Objects exported from other packages
Description
These objects are imported from other packages. Follow the links below to see their documentation.
list(" ", " ", list(list("ggplot2"), list(list(list("facet_grid")))), " ")
setReadable()
setReadable
Description
mapping geneID to gene Symbol
Usage
setReadable(x, OrgDb, keyType = "auto")Arguments
| Argument | Description |
|---|---|
x | enrichResult Object |
OrgDb | OrgDb |
keyType | keyType of gene |
Value
enrichResult Object
Author
Yu Guangchuang
show_methods()
show method
Description
show method for gseaResult instance
show method for enrichResult instance
Usage
show(object)
show(object)Arguments
| Argument | Description |
|---|---|
object | A enrichResult instance. |
Value
message
message
Author
Guangchuang Yu https://guangchuangyu.github.io
Guangchuang Yu https://guangchuangyu.github.io
simplot()
simplot
Description
plotting similarity matrix
Usage
simplot(sim, xlab = "", ylab = "", color.low = "white",
color.high = "red", labs = TRUE, digits = 2, labs.size = 3,
font.size = 14)Arguments
| Argument | Description |
|---|---|
sim | similarity matrix |
xlab | xlab |
ylab | ylab |
color.low | color of low value |
color.high | color of high value |
labs | logical, add text label or not |
digits | round digit numbers |
labs.size | lable size |
font.size | font size |
Value
ggplot object
Author
Yu Guangchuang
summary_methods()
summary method
Description
summary method for gseaResult instance
summary method for enrichResult instance
Usage
summary(object, ...)
summary(object, ...)Arguments
| Argument | Description |
|---|---|
object | A enrichResult instance. |
... | additional parameter |
Value
A data frame
A data frame
Author
Guangchuang Yu https://guangchuangyu.github.io
Guangchuang Yu http://guangchuangyu.github.io
theme_dose()
theme_dose
Description
ggplot theme of DOSE
Usage
theme_dose(font.size = 14)Arguments
| Argument | Description |
|---|---|
font.size | font size |
Value
ggplot theme
Examples
library(ggplot2)
qplot(1:10) + theme_dose()