Package 'meshes'

Title: MeSH Enrichment and Semantic analyses
Description: Provides tools for MeSH (Medical Subject Headings) enrichment and semantic similarity analysis. The package uses MeSH term annotations linked to Entrez Gene identifiers through gendoo, gene2pubmed and RBBH, enabling over-representation analysis, gene set enrichment analysis and semantic comparison of gene lists or ranked expression profiles. It implements Resnik, Schlicker, Jiang, Lin and Wang similarity methods for comparing MeSH terms, genes and gene groups across more than 70 species.
Authors: Guangchuang Yu [aut, cre]
Maintainer: Guangchuang Yu <[email protected]>
License: Artistic-2.0
Version: 1.39.1
Built: 2026-06-30 13:14:39 UTC
Source: https://github.com/bioc/meshes

Help Index

enrichMeSH

Description

MeSH term enrichment analysis

Usage

enrichMeSH(
  gene,
  MeSHDb,
  database = "gendoo",
  category = "C",
  pvalueCutoff = 0.05,
  pAdjustMethod = "BH",
  universe = NULL,
  minGSSize = 10,
  maxGSSize = 500,
  qvalueCutoff = 0.2,
  meshdbVersion = NULL
)

Arguments

gene

a vector of entrez gene id
MeSHDb

MeSHDb
database

one of 'gendoo', 'gene2pubmed' or 'RBBH'
category

one of "A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L","M", "N", "V", "Z"
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 genes annotated for testing
qvalueCutoff

qvalue cutoff
meshdbVersion

version of MeSH.db. If NULL(the default), use the latest version.

Value

An enrichResult instance.

Author(s)

Guangchuang Yu

See Also

class?enrichResult

Examples

## Not run: 
library(meshes)
library(AnnotationHub)
ah <- AnnotationHub()
qr_hsa <- query(ah, c("MeSHDb", "Homo sapiens"))
## inspect qr_hsa and select the organism-specific MeSHDb resource
filepath_hsa <- qr_hsa[[1]]
db <- MeSHDbi::MeSHDb(filepath_hsa)
data(geneList, package="DOSE")
de <- names(geneList)[1:100]
x <- enrichMeSH(de, MeSHDb = db, database='gendoo', category = 'C')

## End(Not run)

geneSim

Description

semantic similarity between two gene vector

Usage

geneSim(geneID1, geneID2 = NULL, measure = "Wang", combine = "BMA", semData)

Arguments

geneID1

gene ID vector
geneID2

gene ID 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.
semData

gene annotation data for semantic measurement

Value

score matrix

Author(s)

Guangchuang Yu

Examples

## library(meshes)
## library(AnnotationHub)
## ah <- AnnotationHub()
## qr_hsa <- query(ah, c("MeSHDb", "Homo sapiens"))
## ## inspect qr_hsa and select the organism-specific MeSHDb resource
## filepath_hsa <- qr_hsa[[1]]
## db <- MeSHDbi::MeSHDb(filepath_hsa)
## hsamd <- meshdata(db, category='A', computeIC=T, database="gendoo")
data(hsamd)
geneSim("241", "251", semData=hsamd, measure="Wang", combine="BMA")

gseMeSH

Description

Gene Set Enrichment Analysis of MeSH

Usage

gseMeSH(
  geneList,
  MeSHDb,
  database = "gendoo",
  category = "C",
  nPerm = 1000,
  exponent = 1,
  minGSSize = 10,
  maxGSSize = 500,
  pvalueCutoff = 0.05,
  pAdjustMethod = "BH",
  verbose = TRUE,
  ...
)

Arguments

geneList

order ranked geneList
MeSHDb

MeSHDb
database

one of 'gendoo', 'gene2pubmed' or 'RBBH'
category

one of "A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L","M", "N", "V", "Z"
nPerm

number of permutations.
exponent

weight of each step
minGSSize

minimal size of each geneSet for analyzing
maxGSSize

maximal size of genes annotated for testing
pvalueCutoff

pvalue Cutoff
pAdjustMethod

pvalue adjustment method
verbose

print message or not
...

other parameter

Value

gseaResult object

Author(s)

Yu Guangchuang

Examples

## Not run: 
library(meshes)
library(AnnotationHub)
ah <- AnnotationHub()
qr_hsa <- query(ah, c("MeSHDb", "Homo sapiens"))
## inspect qr_hsa and select the organism-specific MeSHDb resource
filepath_hsa <- qr_hsa[[1]]
db <- MeSHDbi::MeSHDb(filepath_hsa)
data(geneList, package="DOSE")
y <- gseMeSH(geneList, MeSHDb = db, database = 'gene2pubmed', category = "G")

## End(Not run)

DATA Sets

Description

These datasets are used in meshes

meshdata

Description

construct annoData for semantic measurement

Usage

meshdata(MeSHDb = NULL, database, category, computeIC = FALSE)

Arguments

MeSHDb

MeSHDb package
database

one of supported database
category

one of supported category
computeIC

logical value

Value

a GOSemSimDATA object

Author(s)

Guangchuang Yu

Examples

## Not run: 
library(meshes)
library(AnnotationHub)
ah <- AnnotationHub()
qr_hsa <- query(ah, c("MeSHDb", "Homo sapiens"))
## inspect qr_hsa and select the organism-specific MeSHDb resource
filepath_hsa <- qr_hsa[[1]]
db <- MeSHDbi::MeSHDb(filepath_hsa)
hsamd <- meshdata(db, category='A', computeIC=T, database="gendoo")

## End(Not run)

meshSim

Description

semantic similarity between two MeSH term vectors

Usage

meshSim(meshID1, meshID2, measure = "Wang", semData)

Arguments

meshID1

MeSH term vector
meshID2

MeSH term vector
measure

one of "Wang", "Resnik", "Rel", "Jiang" and "Lin"
semData

annotation data for semantic measurement, output by meshdata function

Value

score matrix

Author(s)

Guangchuang Yu https://guangchuangyu.github.io

Examples

## library(meshes)
## library(AnnotationHub)
## ah <- AnnotationHub()
## qr_hsa <- query(ah, c("MeSHDb", "Homo sapiens"))
## ## inspect qr_hsa and select the organism-specific MeSHDb resource
## filepath_hsa <- qr_hsa[[1]]
## db <- MeSHDbi::MeSHDb(filepath_hsa)
## hsamd <- meshdata(db, category='A', computeIC=T, database="gendoo")
data(hsamd)
meshSim("D000009", "D009130", semData=hsamd, measure="Resnik")