Package 'meshes'

Title: MeSH Enrichment and Semantic analyses
Description: MeSH (Medical Subject Headings) is the NLM controlled vocabulary used to manually index articles for MEDLINE/PubMed. MeSH terms were associated by Entrez Gene ID by three methods, gendoo, gene2pubmed and RBBH. This association is fundamental for enrichment and semantic analyses. meshes supports enrichment analysis (over-representation and gene set enrichment analysis) of gene list or whole expression profile. The semantic comparisons of MeSH terms provide quantitative ways to compute similarities between genes and gene groups. meshes implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively and supports more than 70 species.
Authors: Guangchuang Yu [aut, cre]
Maintainer: Guangchuang Yu <[email protected]>
License: Artistic-2.0
Version: 1.31.1
Built: 2024-07-27 02:38:33 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,
  qvalueCutoff = 0.2,
  minGSSize = 10,
  maxGSSize = 500,
  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
qvalueCutoff

qvalue cutoff
minGSSize

minimal size of genes annotated by Ontology term for testing.
maxGSSize

maximal size of genes annotated for testing
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"))
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"))
## 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",
  exponent = 1,
  minGSSize = 10,
  maxGSSize = 500,
  eps = 1e-10,
  pvalueCutoff = 0.05,
  pAdjustMethod = "BH",
  verbose = TRUE,
  seed = FALSE,
  by = "fgsea",
  meshdbVersion = NULL,
  ...
)

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"
exponent

weight of each step
minGSSize

minimal size of each geneSet for analyzing
maxGSSize

maximal size of genes annotated for testing
eps

This parameter sets the boundary for calculating the p value.
pvalueCutoff

pvalue Cutoff
pAdjustMethod

pvalue adjustment method
verbose

print message or not
seed

logical
by

one of 'fgsea' or 'DOSE'
meshdbVersion

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

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"))
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"))
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"))
## 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")