Package 'loci2path'

eQTL geneset enrichment query demo data

Description

Demo Data to show how to perform eQTL-geneset enrichment query.

Usage

data(loci2path.demo)

Format

An object of class geneSet of length 1.

Details

eqtl.set.list A list of eQTLset objects; eQTL data are collected from GTeX.

biocarta A Geneset object; Geneset are from Broad Institute's MSigDB: curated gene set, category 'cp': BIOCARTA

query.gr A Genomic Region object; Query regions are from immunoBase, crohn's disease.

Examples

data(loci2path.demo)

---

check compatibility of gene identifiers between eQTL set and gene set

Description

This function perform enrichment test between one eQTL set and one gene set

Usage

check.geneid(e.set, g.set)

Arguments

e.set	an eqtlSet object; the eQTL set to be queried against
g.set	an object of geneSet class; the gene set to be tested

Value

a data.frame shows the number of genes from (1) eqtl Set (2) gene Set (3) shared

Examples

check.geneid(eset.list$Skin, biocarta)

---

eqtlSet Class

Description

eqtlSet Class contains information for eqtl-gene association, gene identifier, position of SNPs, etc.

Usage

tissue(x)

eqtlId(x)

eqtlRange(x)

eqtlGene(x)

## S4 method for signature 'eqtlSet'
tissue(x)

## S4 method for signature 'eqtlSet'
eqtlId(x)

## S4 method for signature 'eqtlSet'
eqtlRange(x)

## S4 method for signature 'eqtlSet'
eqtlGene(x)

Arguments

x	An eqtlSet object

Value

Object of class eqtlSet

Slots

tissue

character; name of the cell/tissue of the eQTL study

eqtlId

character; name of the SNPs

eqtlRange

GenomicRanges; position of the SNPs

gene

character; gene identifier

Examples

require(GenomicRanges)
brain.file <- system.file("extdata", "eqtl/brain.gtex.txt", 
    package="loci2path")
tab <- read.table(brain.file, stringsAsFactors=FALSE, header=TRUE)
eqtlRange <- GRanges(seqnames=Rle(tab$snp.chr), 
    ranges=IRanges(start=tab$snp.pos, 
    width=1))
brain.eset <- eqtlSet(tissue="brain",
    eqtlId=tab$snp.id,
    eqtlRange=eqtlRange,
    gene=as.character(tab$gene.entrez.id))
tissue(brain.eset)
head(eqtlId(brain.eset))
eqtlRange(brain.eset)
head(eqtlGene(brain.eset))

---

eQTL geneset enrichment query demo data

Description

Demo Data to show how to perform eQTL-geneset enrichment query.

Usage

data(loci2path.demo)

Format

An object of class list of length 3.

Details

eset.list A list of eQTLset objects; eQTL data are collected from GTeX.

biocarta A Geneset object; Geneset are from Broad Institute's MSigDB: curated gene set, category 'cp': BIOCARTA

query.gr A Genomic Region object; Query regions are from immunoBase, Psoriasis disease.

Examples

data(loci2path.demo)

---

geneSet Class

Description

geneSet Class contains information for names of gene sets and a list of gene sets

Usage

numGene(x)

description(x)

geneSetList(x)

## S4 method for signature 'geneSet'
numGene(x)

## S4 method for signature 'geneSet'
description(x)

## S4 method for signature 'geneSet'
geneSetList(x)

Arguments

x	An geneSet object

Value

Object of class geneSet

Slots

numGene

numeric; the total number of all genes; This number is used in enrichment tests

description

vector of character; additional information for gene sets, such as names, URLs, a short description, etc.

geneSetList

list; a list of gene sets; each member is a vector containing a group of gene identifiers

Examples

biocarta.link.file <- system.file("extdata", 
    "geneSet/biocarta.txt", package="loci2path")
biocarta.link <- read.delim(biocarta.link.file, header=FALSE, 
    stringsAsFactors=FALSE)
biocarta.set.file <- system.file("extdata", "geneSet/biocarta.set.txt", 
    package="loci2path")
set.geneid <- read.table(biocarta.set.file, stringsAsFactors=FALSE)
set.geneid <- strsplit(set.geneid[,1], split=",")
names(set.geneid) <- biocarta.link[,1]
biocarta <- geneSet(
    geneSetList=set.geneid,
    description=biocarta.link[,2],
    numGene=31847)
numGene(biocarta)
head(description(biocarta))
head(geneSetList(biocarta))

---

Generate heatmap of enrichment matrix from query result

Description

This function generate the enrichment heatmap using pheatmap package.

Usage

getHeatmap(res, ...)

## S4 method for signature 'loci2pathResult'
getHeatmap(res, main = "",
  test.method = c("gene", "eqtl", "glm"), filter.quantile = 0.5,
  max.ptw.gene = 5000)

Arguments

res	query result from function query.egset.list()
...	additional params
main	title of the heatmap, default is ""
test.method	Choose which enrichment test should be used to retrive p-values from. Options include:"gene"(default, gene-based fisher's exact test),"eqtl" (eqtl based fisher's exact test), "glm" (ordered query)
filter.quantile	Filter option; choose the max quantile of all p-values being kept in the matrix; default is 0.5, which means p-values larger than median p-values are discarded
max.ptw.gene	Filter option; minimum number of genes in a pathway; default is 5000 (pathway with >5000 genes are not included in the matrix)

Value

pathways	frequent pathways
tissues	frequent tissues

Examples

result <- query(query.gr=query.gr, 
  loci=eset.list, path=biocarta)
getHeatmap(result)

---

Extract tissue/geneset enrichment matrix from query result

Description

This function extracts the enrichment matrix from eQTL list query result. The rows of the matrixs are pathways; and the columns of the matrixs are tissues/cell lines of the eQTL sets. P-Values from enrichment tests are summarized in this matrix

Usage

getMat(res, ...)

## S4 method for signature 'loci2pathResult'
getMat(res, test.method = c("gene", "eqtl",
  "glm"), filter.quantile = 0.5, max.ptw.gene = 5000)

Arguments

res	query result from function query.egset.list()
...	additional params
test.method	Choose which enrichment test should be used to retrive p-values from. Options include:"gene"(default, gene-based fisher's exact test),"eqtl" (eqtl based fisher's exact test), "glm" (ordered query)
filter.quantile	Filter option; choose the max quantile of all p-values being kept in the matrix; default is 0.5, which means p-values larger than median p-values are discarded
max.ptw.gene	Filter option; minimum number of genes in a pathway; default is 5000 (pathway with >5000 genes are not included in the matrix)

Value

p-value matrix collected from enrichment result table

Examples

result <- query(query.gr=query.gr, 
  loci=eset.list, path=biocarta)
mat <- getMat(result, test.method="gene")

---

Extract description for enriched pathways from query result and geneSet object

Description

This function extracts the pathway description from geneSet object.

Usage

getPathDescription(res, ...)

## S4 method for signature 'loci2pathResult'
getPathDescription(res, geneset)

Arguments

res	query result from function query.egset.list()
...	additional params
geneset	A geneSet object

Value

a vector of gene set description from geneSet description slot

Examples

result <- query(query.gr=query.gr, 
  loci=eset.list, path=biocarta)
path.des <- getPathDescription(result, biocarta)

---

Extract tissue/geneset enrichment p-value distribution from query result

Description

This function extracts the enrichment p-value distribution from eQTL list query result. P-values from different tissues/cell types are organized, and QQ-plot is generated against uniform distribution

Usage

getPval(res, ...)

## S4 method for signature 'loci2pathResult'
getPval(res, test.method = c("gene", "eqtl",
  "glm"))

Arguments

res	query result from function query.egset.list()
...	additional params
test.method	Choose which enrichment test should be used to retrive p-values from. Options include:"gene"(default, gene-based fisher's exact test),"eqtl" (eqtl based fisher's exact test), "glm" (ordered query)

Value

generate pval distribution plot

Examples

result <- query(query.gr=query.gr, 
  loci=eset.list, path=biocarta)
getPval(result, test.method="gene")

---

Extract tissue degree from query result

Description

This function extracts the tissue degree from eQTL list query result for each pathway.

Usage

getTissueDegree(res, ...)

## S4 method for signature 'loci2pathResult'
getTissueDegree(res, loci)

Arguments

res	query result from function query.egset.list()
...	additional params
loci	a list of eqtlSet; each member should be an eqtlSet object

Value

gene.tissue.map	shows mapping:gene<->tissue
gene.tissue.degree	shows tissue degree for each gene
mean.tissue.degree	shows the average tissue digree for each pathway in the result table

Examples

result <- query(query.gr=query.gr, 
  loci=eset.list, path=biocarta)
tissue.degree=getTissueDegree(result, eset.list)
head(tissue.degree$gene.tissue.map)
head(tissue.degree$gene.tissue.degree)
head(tissue.degree$mean.tissue.degree)

---

Plot word cloud using frequent terms of pathways and genes

Description

This function draw the enrichment heatmap using wordcloud package.

Usage

getWordcloud(res, ...)

## S4 method for signature 'loci2pathResult'
getWordcloud(res, min.freq.tissue = 5,
  min.freq.gset = 5, max.words = 50)

Arguments

res	query result from function query.egset.list()
...	additional params
min.freq.tissue	minimum frequency of tissue/cell to be plotted in the word cloud
min.freq.gset	minimum frequency of geneset to be plotted in the word cloud
max.words	maximum words to be generated

Value

empty

Examples

result <- query(query.gr=query.gr, 
  loci=eset.list, path=biocarta)
getWordcloud(result, min.freq.tissue=2, min.freq.gset=1)

---

loci2pathResult Class

Description

loci2pathResult Class contains information for the query result from query function query. Result object contains a ranked pathway table, and a vector of gene names that are associated with loci covered by query regions

Usage

resultTable(x)

coveredGene(x)

## S4 method for signature 'loci2pathResult'
resultTable(x)

## S4 method for signature 'loci2pathResult'
coveredGene(x)

Arguments

x	An geneSet object

Value

Object of CLass loci2pathResult

Slots

resultTable

data.frame; contains enrichment statistics, summary of eQTL and gene numbers, pathway names and gene names, etc.

coveredGene

list; each member is a vector of genes associated with one tissue, whose associating loci are covered by query regions

Examples

result <- query(query.gr=query.gr, 
  loci=eset.list, path=biocarta)
result
resultTable(result) # a data.frame for enriched pathways
coveredGene(result)

---

Query enrichment in geneset through multiple eQTL sets.

Description

This is the main function for loci2path query. Query can be made on either pathway enrichment or tissue-specificity, depending on the input Class. See Details for more.

Usage

query(query.gr, loci, path, ...)

## S4 method for signature 'GenomicRanges,list,ANY'
query(query.gr, loci, N = 2897310462)

## S4 method for signature 'GenomicRanges,eqtlSet,geneSet'
query(query.gr, loci, path,
  query.score = NULL, verbose = FALSE)

## S4 method for signature 'GenomicRanges,list,geneSet'
query(query.gr, loci, path,
  query.score = NULL, parallel = FALSE, verbose = FALSE)

Arguments

query.gr	a GenomicRange object, representing query regions
loci	a list of eqtlSet; each member should be an eqtlSet; Or it can be a single eqtlSet.
path	Pathways or geneSets to be tested for enrichment
...	additional params
N	the total number of non-N nucleotides in the genome; default N=2897310462 is for hg19
query.score	optional, set to NULL if the regions are not ordered. If the query regions are ordered, query.score is the quantity based on which the regions are ordered
verbose	bool; whether to show eqtlSet/geneSet summary information; default is FALSE
parallel	bool; whether to enable parallel computing; default is FALSE

Details

The user need to specify

1. Query region;

2. loci; one or more eQTL set; this is usually more than one eQTL set. Only multiple eQTL set derived from different cells/tissues will show cell/tissue specificity.

3. path; pre-defined Pathways, or gene sets. the gene sets that enrichment tests would be performed to.

loci must be provided; path is optional. When path is missing, the tissue-specificity query for the regions is performed.

The most common case for loci is an eQTL set list. This function perform enrichment test between one eQTL set and a group of gene sets. Usually query are based on eQTL set list, rather than only one eQTL set. Several result exploring functions (getMat, getHeatmap, getPval, etc...) are designed for query result from eQTL set list and gene sets. The class loci2pathResult is also designed for eQTL set list query result only. The result returns a loci2pathResult only the class of loci is a list of eqtlSet.

If user input one eQTL set as argument loci, a simple list object will be returned for specific research purpose.

Value

a data.frame showing the tissue enrichment of the query regions by binomial test.

a list; result.table is the major result table showing enrichment assessment; cover.gene is the vector showing the genes from the eqtl Sets covered by the query region(s)

a loci2pathResult class object

See Also

loci2pathResult

Examples

gr.tissue <- query(query.gr, eset.list)
#build one eqtlset
skin.eset <- eset.list$Skin
#query one egset
res.one <- query(query.gr, skin.eset, biocarta)
#enrichment result table
res.one$result.table
#all the genes associated with eQTLs covered by the query region
res.one$cover.gene
result <- query(query.gr=query.gr,
    loci=eset.list, path=biocarta)
#enrichment result table
resultTable(result)
#all the genes associated with eQTLs covered by the query region
coveredGene(result)

---

eQTL geneset enrichment query demo data

Description

Demo Data to show how to perform eQTL-geneset enrichment query.

Usage

data(loci2path.demo)

Format

An object of class GRanges of length 47.

Details

eqtl.set.list A list of eQTLset objects; eQTL data are collected from GTeX.

biocarta A Geneset object; Geneset are from Broad Institute's MSigDB: curated gene set, category 'cp': BIOCARTA

query.gr A Genomic Region object; Query regions are from immunoBase, crohn's disease.

Examples

data(loci2path.demo)

---