Provides statistics on the types of ids used for the ACCNUM environment of a given data package

Description

Given a data package name, ACCNUMStats counts how many of the probe ids are mapped to GenBank Accession numbers, UniGene ids, RefSeq ids, or Image clone ids.

Usage

ACCNUMStats(pkgName)
whatACC(accs)

Arguments

Details

The ACCNUM environment of each BioC data package contains mappings between probe ids and a set of public ids based on which mappings of probe ids to other annotation data can be obtained using public data sources. The set of ids were provided by a manufacturer or user at the time when the data package was built. The manufacturer/user provided ids can be of different types of public ids, such as GenBank Accession number, UniGene ids, etc..

ACCNUMStats counts the number of probes that are mapped to different types of public ids and have the results presented in a table.

Author

Jianhua Zhang

References

The ACCNUM environment of a platform dependent BioC data package

Examples

library("hgu95av2.db")
ACCNUMStats("hgu95av2")

Compute a heatmap for the specified data, for either a GO category or a KEGG pathway.

Description

For a given GO category or KEGG pathway, all probes in the supplied data are mapped to the pathway and a heatmap is produced.

Usage

GO2heatmap(x, eset, data, ...)
KEGG2heatmap(x, eset, data, ...)

Arguments

Details

For the given pathway or GO category all matching probes are determined, these are used to subset the data and heatmap is invoked on that set of data. Extra parameters can be passed through to heatmap using the list() parameter. The annotation slot of the eset argument is used to determine the appropriate annotation data to use.

Value

The value returned by heatmap is passed back to the user.

Seealso

heatmap

Author

R. Gentleman

Examples

library("hgu95av2.db")
data(sample.ExpressionSet)
KEGG2heatmap("04810", sample.ExpressionSet, "hgu95av2")

A function to plot by group means against each other.

Description

For a two sample comparison, as determined by group , and a specified KEGG pathway or GO category, per group means are computed and plotted against each other.

Usage

GOmnplot(x, eset, data = "hgu133plus2", group, ...)
KEGGmnplot(x, eset, data = "hgu133plus2", group, ...)

Arguments

Details

All probes in eset that map to the given category are determined. Then per group, per probe means are computed and plotted against each other. Extra parameters can be passed to the plot function via the dots argument.

Value

The matrix of per group means, for each probe.

Seealso

KEGG2heatmap

Author

R. Gentleman

Examples

library("hgu95av2.db")
data(sample.ExpressionSet)
KEGGmnplot("04810", sample.ExpressionSet, sample.ExpressionSet$sex,
data = "hgu95av2")

Classes to represent HTML pages

Description

Class HTMLPage and FramedHTMLPage are a pair of experimental classes used to explore concepts of representing HTML pages using S4 objects.

Note

These classes are currently experimental.

FramedHTMLPage is modeled after the framing layout of the Bioconductor website (www.bioconductor.org).

Author

Jeff Gentry

Examples

##---- Should be DIRECTLY executable !! ----

DEPRECATED Functions that find the homology data for a given set of LocusLink ids or HomoloGeneIDs

Description

These functions are DEPRECATED. All this functionality has been replaced by inPARANOID packages. Given a set of LocusLink ids or NCBI HomoloGeneIDs, the functions obtain the homology data and represent them as a list of sub-lists using the homology data package for the organism of interest. A sub-list can be of length 1 or greater depending on whether a LocusLink id can be mapped to one or more HomoloGeneIDs.

Usage

LL2homology(homoPkg, llids)
HGID2homology(hgid, homoPkg)
ACC2homology(accs, homoPkg)

Arguments

Details

The homology data package has to be installed before executing any of the two functions.

Each sub-list has the following elements:

homoOrg - a named vector of a single character string whose value is the scientific name of the organism and name the numeric code used by NCBI for the organism.

homoLL - an integer for LocusLink id.

homoHGID - an integer for internal HomoloGeneID.

homoACC - a character string for GenBank accession number of the best matching sequence of the organism.

homoType - a single letter for the type of similarity measurement between the homologous genes. homoType can be either B (reciprocal best best between three or more organisms), b (reciprocal best match between two organisms), or c (curated homology relationship between two organisms).

homoPS - a percentage value measured as the percent of identity of base pair alignment between the homologous sequences.

homoURL - a url to the source if the homology relationship is a curated orthology.

Sub-lists with homoType = B or b will not have any value for homoURL and objects with homoType = c will not have any value for homoPS.

Value

Both functions returns a list of sub-lists containing data for homologous genes in other organisms.

Author

Jianhua Zhang

References

https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?=homologene

Examples

## hsahomology is a deprecated package!
if(require("hsahomology")){
llids <- ls(env = hsahomologyLL2HGID)[2:5]
LL2homology("hsahomology", llids)
}

A function to compute the probe to PubMed id incidence matrix.

Description

For a given chip or a given set of genes, it computes the mapping from probes to PubMed id.

Usage

PMIDAmat(pkg, gene=NULL)

Arguments

Details

Not much to say, just find which probes are associated with which PubMed ids and return the incidence matrix, with PubMed ids as rows and probes as columns.

To specify a set of probes to use, let the argument gene to be a vector of probe ids. Bt this way, the calculations are not involved with non-interested genes/PubMed ids so that the whole process could finish soon.

Value

A matrix containing zero or one, depending on whether the probe (column) is associated with a PubMed id (row).

Author

R. Gentleman

Examples

library("hgu95av2.db")
probe <- names(as.list(hgu95av2ACCNUM))
Amat <- PMIDAmat("hgu95av2", gene=sample(probe, 10))

A function to compute the probe to KEGG pathway incidence matrix.

Description

For a given chip we compute the mapping from probes to KEGG pathways.

Usage

PWAmat(data)

Arguments

Details

Not much to say, just find which probes are in which pathways and return the incidence matrix, with pathways as rows and probes as columns.

It would be nice to be able to specify a set of probes to use, so that one does not do perform the calculations using all probes if they are not of interest.

Value

A matrix containing zero or one, depending on whether the probe (row) is in a pathway (column).

Seealso

KEGG2heatmap , GOmnplot

Author

R. Gentleman

Examples

library("hgu95av2.db")
Am1 <- PWAmat("hgu95av2")

Create a Query String for a UniGene Identifier

Description

Given a set of UniGene identifiers this function creates a set of URLs that an be used to either open a browser to the requested location or that can be used as anchors in the construction of HTML output.

Usage

UniGeneQuery(query, UGaddress="UniGene/", type="CID")

Arguments

Details

Using published details from NCBI we construct an appropriate string for directing a web browser to the information available at the NCBI for that genomic product (usually an EST).

Value

A character vector containing the query string.

Note

Be very careful about automatically querying this resource. It is considered antisocial behavior by the owners.

Author

Robert Gentleman

References

NCBI, https://www.ncbi.nih.gov/

Examples

q1<-UniGeneQuery(c("Hs.293970", "Hs.155650"))
q1
if( interactive())
browseURL(q1[1])

A function to convert accession values to NCBI UIDs.

Description

Given one or more accession values, this function will attempt to convert them into NCBI UID values.

Usage

accessionToUID(...,db=c("genbank","pubmed"))

Arguments

Details

Utilizes the PubMed tool esearch.fcgi to convert an accession number into a valid NCBI UID number.

WARNING: The powers that be at NCBI have been known to ban the IP addresses of users who abuse their servers (currently defined as less then 2 seconds between queries). Do NOT put this function in a type loop or you may find your access revoked.

Value

Returns either a valid NCBI UID value or NULL (if there was nothing available).

Seealso

pubmed , xmlTreeParse

Author

Jeff Gentry

Examples

## The two returns from genbank should be the same
xdoc <- genbank("U03397",type="accession",disp="data")
x <- accessionToUID("U03397",db="genbank")
xdoc <- genbank(x, type="uid",disp="data")

## Can handle multiple inputs
y <- accessionToUID("M16653","U892893",db="genbank")

Get annotation package name from chip name

Description

This function returns the name of the Bioconductor annotation data package that corresponds to the specified chip or genome. The type argument is used to request an annotation package with a particular backing store.

Usage

annPkgName(name, type = c("db", "env"))

Arguments

Value

a string giving the name of the annotation data package

Seealso

getAnnMap

Author

Seth Falcon

Examples

annPkgName("hgu133plus2", type="db")
annPkgName("hgu133plus2", type="env")

Defunct Functions in Package annotate

Description

The functions or variables listed here are no longer part of the annotate package.

Usage

neighborGeneFinder()
genelocator()
getQuery4LL()
probesByLL()

Seealso

Defunct

List GO Identifiers by GO Ontology

Description

This function returns a character vector of all GO identifiers in the specified ontologies: Biological Process (BP), Cellular Component (CC), Molecular Function (MF).

Usage

aqListGOIDs(ont)

Arguments

Value

A character vector of GO IDs. The vector will contain all GO IDs in the GO ontologies specified by the ont argument.

Author

Seth Falcon

Examples

## all GO IDs in BP
bp_ids = aqListGOIDs("BP")
length(bp_ids)

## all GO IDs in BP or CC
bp_or_cc_ids = aqListGOIDs(c("BP", "CC"))
length(bp_or_cc_ids)

Run a blast query to NCBI for either a string or an entrez gene ID and then return a series of MultipleAlignment objects.

Description

This function sends a query to NCBI as a string of sequence or an entrez gene ID and then returns a series of MultipleAlignment objects.

Usage

blastSequences(x, database, hitListSize, filter, expect, program,
      timeout=40, as=c("DNAMultipleAlignment", "data.frame", "XML"))

Arguments

|x | A sequence as a character vector or an integer corresponding to an entrez gene ID. Submit multiple sequences as a length-1 character vector, x = ">ID-1 ACATGCTA >ID-2 AAACCACTT" . | |database | Which NCBI database to use. If not blastn , then set as="XML" | |hitListSize | Number of hits to keep. | |filter | Sequence filter; L for Low Complexity, R for Human Repeats, m for Mask lookup | |expect | The BLAST expect value above which matches will be returned. | |program | Which program do you want to use for blast. | |timeout | Approximate maximum length of time, in seconds, to wait for a result. | |as | character(1) indicating whether the result from the NCBI server should be parsed to a list of DNAMultipleAlignment instances, represented as a data.frame , or returned as XML. |

Details

Right now the function only works for "blastn".

The NCBI URL api used by this function is documented at https://www.ncbi.nlm.nih.gov/blast/Doc/urlapi.html

Value

By default, a series of DNAMultipleAlignment (see MultipleAlignment-class objects. Alternatively, a data.frame or XML document returned from the NCBI server. The data.frame is a long form representation of the Iteration , Hit and Hsp results returned from the server. The XML document is the result of the xmlParse function of the XML library, and follows the format described by https://www.ncbi.nlm.nih.gov/dtd/NCBI_BlastOutput.dtd and https://www.ncbi.nlm.nih.gov/dtd/NCBI_BlastOutput.mod.dtd .

Author

M. Carlson

Examples

## x can be an entrez gene ID
blastSequences(17702, timeout=40, as="data.frame")

if (interactive()) {

## or x can be a sequence
blastSequences(x = "GGCCTTCATTTACCCAAAATG")

## hitListSize does not promise that you will get the number of
## matches you want..  It will just try to get that many.
blastSequences(x = "GGCCTTCATTTACCCAAAATG", hitListSize="20")

}

A function to generate an instantiation of a chromLocation class

Description

This function will take the name of a data package and build a chromLocation object representing that data set.

Usage

buildChromLocation(dataPkg)

Arguments

Details

The requested data set must be available in the user's .libPaths() , and the function will throw an error if this is not the case.

If the data package is present, the necessary information will be extracted from the data package and a chromLocation object will be created.

Value

A chromLocation object representing the specified data set.

Author

Jeff Gentry

Examples

library("hgu95av2.db")
z <- buildChromLocation("hgu95av2")

A function to generate an instantiation of a pubMedAbst class

Description

This function will take in a XML tree object and will create an instance of a pubMedAbst class. This instance is returned to the caller.

Usage

buildPubMedAbst(xml)

Arguments

Value

This function returns an instantiation of a pubMedAbst object to the caller.

Seealso

pubmed , genbank

Author

Jeff Gentry

Examples

x <- pubmed("9695952","8325638","8422497")
a <- xmlRoot(x)
numAbst <- length(xmlChildren(a))
absts <- list()
for (i in 1:numAbst) {
absts[[i]] <- buildPubMedAbst(a[[i]])
}

Returns a list of chromosome locations from a MAP environment

Description

The chrCats function takes a data package that contains a MAP environment and returns a list that contains the locations for each gene (from the chromosome number to more specific locations if they're available). For example, the hgu95av2MAP environment gives the location, 14q22-q23, for Affymetrix identifier: 1114_at. This function will return a list with one named element for 1114_at and the values it will contain are 14, 14q, 14q2, 14q22, and 14q23 since the Affy id is located at each of those chromosome locations.

Usage

chrCats(data)
createMAPIncMat(data)
createLLChrCats(data)

Arguments

Details

This function does a lot of string manipulation and there are a few known errors so I want to discuss them here in case someone else would like to improve on this function.

The first thing, chrCats, does is only allow one location for each Affymetrix identifier. If the MAP environment has more than one location for an Affy id, then the first location is taken. Currently, the hgu95av2MAP environment has only 9 Affy ids (out of 12625) that have more than one location and the hgu133aMAP environment has only 16 Affy ids (out of 22283) that have more than one location so this does not affect many identifiers.

Next any spaces are removed from each location as several locations have leading spaces.

Then a for loop (which is not efficient!) is used to look at each location individually and make a list that will be returned. A few particular | strings are looked for in each location and these include |' and-'.|

| Locations that include |' in the string are split based on the|' as| though it represents OR. For example, for Affy id, 32273_at, in hgu95av2MAP | the location is given as 5q33|5q31.1 and this function assumes this means| 5q33 or 5q31.1 so it will return the values 5, 5q, 5q3, 5q33, 5q31, and 5q31.1 for this Affy id.

The -' character is assumed to mean BETWEEN. For example, for Affy id, 1138_at, in hgu95av2MAP the location is given as 2q11-q14 and this function assumes this means the location is somewhere between 2q11 and 2q14 so it will return the values 2, 2q, 2q1, 2q11, 2q12, 2q13, and 2q14 for this Affy id. Now here is the first problem with this function. I do not know how to handle the-' when the two strings are not of equal length. For example, for Affy id, 36779_at, in hgu95av2MAP the location is given as 5q33.3-q34, but I do not know how to treat this BETWEEN because I do not know how many sub-bands there are between 5q33.3 and 5q34. Is there a 5q33.4 or 5q33.5, | etc.? I'm not sure. So I treat this -' as an|'. This function will| return the values 5, 5q, 5q3, 5q33, 5q33.3, and 5q34 for this Affy id and most likely, that is incorrect.

Another problem I have with the -' occurs when all of the characters up until the last character do not match. For example, for Affy id, 38927_i_at, in hgu95av2MAP the location is given as 11q14-q21, but again I'm not sure how to treat this BETWEEN because I don't know the number of sub-bands between 11q14 and 11q21. Does 11q15 exist, etc.? So I again | treat this-' as an |'. This function will return the values 11, 11q,| 11q1, 11q14, 11q2, and 11q21 for this Affy id and this is probably incorrect. The problem with-' also occurs when the location is something like 19cen-q13.1 for Affy id, 34670_at, in hgu95av2MAP. Again I don't know the number of sub-bands between 19cen and 19q13.1 so I treat this BETWEEN as an OR.

Another problem I have with cen' in the location is that sometimes the location looks like: 19p13.2-cen and very rarely it looks like: 5p13.1-5cen. In the second case, the chromosome number is included after the-' and before the cen'. This only occurs with the location 5p13.1-5cen in both hgu95av2MAP and hgu133aMAP and all other locations do not include the chromosome number after the-'. Currently this function returns the wrong information for that one location. It will return the values 5, 5p, 5p1, 5p13, 5p13.1, 5p5,and 5p5cen, but it should return 5, 5p, 5p1, 5p13, 5p13.1, and 5cen so this one location is an error. All other locations that include cen' are correct. For example, this function returns the values 19, 19p, 19p1, 19p13, 19p13.2, and 19cen for the location 19p13.2-cen. This function is very slow because it contains for loops and thus, it would be useful to make it more efficient. Also, it would be nice at some point for someone with more knowledge on chromosome location figure out how to improve some of my string manipulation errors.createLLChrCatsis a wrapper that converts probe IDs to Entrez Gene IDs.createMAPIncMatis a wrapper that callscreateLLChrCats` and then returns an incidence matrix with rows being the categories and cols the Entrez Gene IDs. ## Value A named list with an element for each Affy id. The name will be the Affy id and the values will be the locations for that Affy id. If the Affy id had a location of NA in the MAP environment, then a list element is not returned for that Affy id. ## Author Elizabeth Whalen ## Examples r library("hgu95av2.db") mapValues <- chrCats("hgu95av2")

Class chromLocation, a class for describing genes and their chromosome mappings.

Description

This class provides chromosomal information provided by a Bioconductor metadata package. By creating the object once for a particular package, it can be used in a variety of locations without the need to recomputed values repeatedly.

Seealso

buildChromLocation

Examples

library("hgu95av2.db")

z <- buildChromLocation("hgu95av2")

## find the number of chromosomes
nChrom(z)

## Find the names of the chromosomes
chromNames(z)

## get the organism this object refers to
organism(z)

## get the lengths of the chromosomes in this object
chromLengths(z)

function to check to see if the packages represented by the names passed have the same version number

Description

This function takes the names of installed R packages and then checks to see if they all have the same version number.

Usage

compatibleVersions(...)

Arguments

Details

If all the package have the same version number, the function returns TRUE. Otherwise, the function returns FALSE

Value

This function returns TRUE or FALSE depending on whether the packages have the same version number

Seealso

packageDescription

Author

Jianhua Zhang

Examples

library("hgu95av2.db")
library("GO.db")
compatibleVersions("hgu95av2.db", "GO.db")

Drop GO labels for specified Evidence Codes

Description

Genes are mapped to GO terms on the basis of evidence codes. In some analyses it will be appropriate to drop certain sets of annotations based on specific evidence codes.

Usage

dropECode(inlist, code="IEA")

Arguments

Details

A simple use of lapply and sapply to find and eliminate those terms that have the specified evidence codes.

This might be used when one is using to GO to validate a sequence matching experiment (for example), then all terms whose mapping was based on sequence similarity (say ISS and IEA) should be removed.

Value

A list of the same length as the input list retaining only those annotations whose evidence codes were not the ones in the exclusion set code .

Seealso

getEvidence , getOntology

Author

R. Gentleman

Examples

library("hgu95av2.db")
bb <- hgu95av2GO[["39613_at"]]
getEvidence(bb[1:3])
cc <- dropECode(bb[1:3])
if (length(cc))
getEvidence(cc)

Create a Query String for an Entrez Gene Identifier

Description

Given a set of UniGene identifiers this function creates a set of URLs that an be used to either open a browser to the requested location or that can be used as anchors in the construction of HTML output.

Usage

entrezGeneByID(query)

Arguments

Details

Using NCBI we construct appropriate strings for directing a web browser to the Entrez Genes specified by their IDs.

Value

A character vector containing the query string.

Note

Be very careful about automatically querying this resource. It is considered antisocial behavior by the owners.

Author

Marc Carlson

References

NCBI, https://www.ncbi.nih.gov/

Examples

q1<-entrezGeneByID(c("100", "1002"))
q1
if( interactive())
browseURL(q1[1])

Create a Query String for Entrez Genes

Description

Given a set of search terms this function creates a set of URLs that an be used to either open a browser to the requested location or that can be used as anchors in the construction of HTML output.

Usage

entrezGeneQuery(query)

Arguments

Details

Using NCBI we construct an appropriate string for directing a web browser to information about genes of that type at NCBI.

Value

A character vector containing the query string.

Note

Be very careful about automatically querying this resource. It is considered antisocial behavior by the owners.

Author

Marc Carlson

References

NCBI, https://www.ncbi.nih.gov/

Examples

q1<-entrezGeneQuery(c("leukemia", "Homo sapiens"))
q1
if( interactive())
browseURL(q1[1])

Filter GO terms by a specified GO ontology

Description

Given a character vector containing GO identifiers, return a logical vector indicating which GO IDs are in the specified ontology (BP, CC, or MF).

Usage

filterGOByOntology(goids, ontology = c("BP", "CC", "MF"))

Arguments

Value

A logical vector with length equal to goids . A TRUE indicates that the corresponding GO ID in goids is a member of the ontology specified by ontology .

Author

Seth Falcon

Examples

haveGO <- suppressWarnings(require("GO.db"))
if (haveGO) {
ids <- c("GO:0001838", "GO:0001839")
stopifnot(all(filterGOByOntology(ids, "BP")))
stopifnot(!any(filterGOByOntology(ids, "MF")))
} else cat("Sorry, this example requires the GO package
")

A function to locate neighboring genes within a defined range around a target gene represented by a Entrez Gene ID

Description

Give a data package with mappings between Entrez Gene IDs and their locations on chromosomes, this function locates genes that are within a defined range on a given chromosome. If a Entrez Gene ID is passed as one of the arguments, genes located will be neighbors to the gene represented by the Entrez Gene ID within a defined range on the chromosome the target gene resides

Usage

findNeighbors(chrLoc, llID, chromosome, upBase, downBase, mergeOrNot = TRUE)
checkArgs(llID, chromosome, upBase, downBase)
findChr4LL(llID, chrEnv, organism)
getValidChr(organism)
getBoundary(loc, base, lower = TRUE)
weightByConfi(foundLLs)

Arguments

Details

A chrLoc data package can be created using function chrLocPkgBuilder of AnnBuilder, in which Entrez Gene IDs are mapped to location data on individual chromosomes.

Genes are considered to be neighbors to a given target gene or within a given range when the transcription of genes start and end within the given range.

findNeighbors, checkArgs, findChr4LL, getValidChr, and getBoundary are accessory functions called by findNeighbors and may not have real values outside.

Value

The function returns a list of named vectors. The length of the list is one when genes in a given region are sought but varies depending on whether a given gene can be mapped to one or more chromosomes when neighboring genes of a target gene are sought. Names of vector can be "Confident" when a gene can be confidently placed on a chromosome or "Unconfident" when a gene can be placed on a chromosome but its exact location can not be determined with great confidence.

Author

Jianhua Zhang

References

http://www.genome.ucsc.edu/goldenPath/

Examples

if(require("humanCHRLOC")){
findNeighbors("humanCHRLOC", "51806", 10, upBase = 600000, downBase = 600000)
}else{
print("Can not find neighbors without the required data package")
}

A function to open the browser to Genbank with the selected gene.

Description

Given a vector of Genbank accession numbers or NCBI UIDs, the user can either have a browser display a URL showing a Genbank query for those identifiers, or a XMLdoc object with the same data.

Usage

genbank(...,disp=c("data","browser"), type=c("accession","uid"),
        pmaddress=.efetch("gene", disp, type))

Arguments

Details

A simple function to retrieve Genbank data given a specific ID, either through XML or through a web browser. This function will accept either Genbank accession numbers or NCBI UIDs (defined as a Pubmed ID or a Medline ID) - although the types must not be mixed in a single call.

WARNING: The powers that be at NCBI have been known to ban the IP addresses of users who abuse their servers (currently defined as less then 2 seconds between queries). Do NOT put this function in a tight loop or you may find your access revoked.

Value

If the option "data" is used, an object of type XMLDoc is returned, unless there was an error with the query in which case an object of type try-error is returned.

If the option "browser" is used, nothing is returned.

Seealso

pubmed , xmlTreeParse

Author

R. Gentleman

Examples

## Use UIDs to get data in both browser & data forms

if ( interactive() ) {
disp <- c("data","browser")
} else {
disp <- "data"
}

for (dp in disp)
genbank("12345","9997",disp=dp,type="uid")

## Use accession numbers to retrieve browser info
if ( interactive() )
genbank("U03397","AF030427",disp="browser")

Get annotation map

Description

This function retrieves a map object from an annotation data package. It is intended to serve as a common interface for obtaining map objects from both SQLite-based and environment-based annotation data packages.

Usage

getAnnMap(map, chip, load = TRUE, type = c("db", "env"))

Arguments

Details

getAnnMap uses the search path (see search ) to find an appropriate annotation data package; when called with chip="hgu95av2" , the function will use the first hgu95av2 package on the search path whether it be db or environment-based. If load=TRUE and no suitable package is found on the search path, then the function will attempt to load an appropriate package. The type argument is used to determine which type of package (db or env) is loaded first.

Value

If type is "db" , an S4 object representing the requested map. If type is "env" , an R environment object representing the requested map.

Author

Seth Falcon

Examples

map <- getAnnMap("ENTREZID", "hgu95av2", load=TRUE, type=c("env", "db"))
class(map)

Get the Evidence codes for a set of GO terms.

Description

For each mapping of a gene to a GO term there are a set of evidence codes that are used. Genes can be mapped using one, or more evidence codes and this function obtains the evidence codes for all genes provided in the input list.

Usage

getEvidence(inlist)

Arguments

Value

A list of the same length as the input list, each element is a vector of evidence codes.

Seealso

getOntology , dropECode

Author

R. Gentleman

Examples

library("hgu95av2.db")
bb <- hgu95av2GO[["39613_at"]]
getEvidence(bb)

Functions to Access GO data.

Description

These functions provide access to data in the GO package. The data are assembled from publically available data from the Gene Ontology Consortium (GO), www.go.org . Given a list of GO identifiers they access the children (more specific terms), the parents (less specific terms) and the terms themselves.

Usage

getGOTerm(x)
getGOParents(x)
getGOChildren(x)
getGOOntology(x)

Arguments

Details

GO consists of three (soon to be more) specific hierarchies: Molecular Function (MF), Biological Process (BP) and Cellular Component (CC). For more details consult the GO website. For each GO identifier each of these three hierarchies is searched and depending on the function called the appropriate values are obtained and returned.

It is possible for a GO identifier to have no children or for it to have no parents. However, it must have a term associated with it.

Value

A list of the same length as x . The list contains one entry for each element of x . That entry is itself a list. With one component named Ontology which has as its value one of MF, BP or CC. The second component has the same name as the suffix of the call, i.e. Children, Parents, or Term. If there was no match in any of the ontologies then a length zero list is returned for that element of x .

For getGOOntology a vector of categories (the names of which are the original GO term names). Elements of this list that are NA indicate term names for which there is no category (and hence they are not really term names).

Author

R. Gentleman

References

The Gene Ontology Consortium

Examples

library("GO.db")

sG <- sample(keys(GO.db, "GOID"), 8)

gT <- getGOTerm(sG)
gP <- getGOParents(sG)
gC <- getGOChildren(sG)
gcat <- getGOOntology(sG)

Get GO terms for a specified ontology

Description

Find the subset of GO terms for the specified ontology, for each element of the supplied list of associations. The input list is typically from one of the chip-specific meta-data files.

Usage

getOntology(inlist, ontology=c("MF", "BP", "CC"))

Arguments

Details

The input list should be a list of lists, each element of inlist is itself a list containing the information that maps from a specified ID (usually LocusLink) to GO information. Each element of the inner list is a list with elements GOID , Ontology and Evidence .

Value

A list of the same length as the input list. Each element of this list will contain a vector of GOID s for those terms that match the requested ontology.

Seealso

getEvidence , dropECode

Author

R. Gentleman

Examples

library("hgu95av2.db")
bb <- hgu95av2GO[["39613_at"]]
getOntology(bb)
sapply(bb, function(x) x$Ontology)

extract publication details and abstract from annotate::pubmed function output

Description

extract publication details and abstract from annotate::pubmed function output

Usage

getPMInfo(x)

Arguments

Details

uses xmlDOMApply to extract and structure key features of the XML tree returned by annotate::pubmed()

Value

a list with one element per pubmed id processed by pubmed. Each element of the list is in turn a list with elements for author list, title, journal info, and abstract text.

Note

this should be turned into a method returning an instance of a formal class representing articles.

Author

Vince Carey stvjc@channing.harvard.edu

Examples

demo <- pubmed("11780146",
"11886385", "11884611")
getPMInfo(demo)

Functions to deal with Data Packages

Description

The functions documented here are intended to make it easier to map from a set of manufacturers identifiers (such as you will get from the chips etc) to other identifiers.

Usage

getSYMBOL(x, data)
getLL(x, data)
getEG(x, data)
getGO(x, data)
getPMID(x, data)
getGOdesc(x, which)
lookUp(x, data, what, load = FALSE)
getUniqAnnItem()

Arguments

Details

Users must supply the basename of the meta-data package that they want to use to provide the mappings. The name of the meta-data package is the same as the basename.

Appropriate translations are done. In some cases such as getEG and getSYMBOL there will only be one match and a vector is returned. In other cases such as getPMID and getGO there may be multiple matches and a list is returned.

For getGOdesc x contains GO identifiers (not manufacturer identifiers) and the output is a list of GOTerms objects, if which specifies some subset of the ontologies (MF, BP or CC) then only terms for that ontology are retained.

lookUp is a general function that can be used to look up matches. All other translation functions use lookUp

A BioC annotation data package contains annotation data environments whose names are package name (e. g. hgu95av2) + element name (e. g. PMID). what must be one of the element names for the given data package.

getUniqAnnItem keeps track of the annotation elements that have one to one mappings.

Value

Either a vector or a list depending on whether multiple values per input are possible.

Seealso

mget

Author

R. Gentleman

Examples

library("hgu95av2.db")
library("GO.db")

data(sample.ExpressionSet)
gN <- featureNames(sample.ExpressionSet)[100:105]
lookUp(gN, "hgu95av2", "SYMBOL")

# Same as lookUp for SYMBOL except the return is a vector
getSYMBOL(gN,"hgu95av2" )
gg <- getGO(gN, "hgu95av2")
lookUp(gg[[2]][[1]][["GOID"]], "GO", "TERM")

# Same as lookUp for TERM
getGOdesc(gg[[2]][[1]][["GOID"]], "ANY")

# For BP only
getGOdesc(gg[[2]][[1]][["GOID"]], "BP")
getEG(gN, "hgu95av2")
getPMID(gN, "hgu95av2")

Queries the NCBI database to obtain the sequence for a given GenBank Accession number

Description

Given a GenBank Accession number, getSEQ queries the NCBI database for the nucleotide sequence.

Usage

getGI(accNum)
getSEQ(gi)

Arguments

Details

The NCBI database is queried for the given GenBank Accession number to obtain the nucleotide sequence in FASTA format. The leading identification line of the sequence data is then dropped to return only the nucleotide sequence.

getGI returns the gi number corresponding to a given GenBank accession number.

Value

getSEQ returns a character string of nucleotide sequence

Author

Jianhua Zhang

References

https://www.ncbi.nlm.nih.gov/entrez/query.fcgi

Examples

getSEQ("M22490")

Functions to create hypertext links that can be placed in a table cell of a HTML file

Description

Given a vector of ids, the functions will create a vector of hypertext links to a defined public repositories such as LocusLink, UniGene .... The linkages can be placed in a html file constructed by htmlpage

Usage

getQueryLink(ids, repository = "ug", ...)
getTDRows(ids, repository = "ug", ...)
getCells(ids, repository = "ug", ...)
getQuery4UG(ids, ...)
getQuery4SP(ids, ...)
getQuery4GB(ids, ...)
getQuery4OMIM(ids, ...)
getQuery4Affy(ids, ...)
getQuery4FB(ids, ...)
getQuery4EN(ids, ...)
getQuery4TR(ids, ...)
getQuery4ENSEMBL(ids, ...)

Arguments

Details

getQuery4GB constructs hypertext links to GenBank using the provided ids.

getQuery4UG constructs hypertext links to UniGene using the provided ids.

getQuery4Affy constructs hypertext links to Affymetrix using the provided ids.

getQuery4SP constructs hypertext links to SwissProt using the provided ids.

getQuery4OMIM constructs hypertext links to OMIM using the provided ids.

getQuery4FB constructs hypertext links to FlyBase using the provided ids.

getQuery4EN constructs hypertext links to EntrezGene using the provided ids.

getQuery4TR constructs hypertext links to TAIR using the provided ids.

getQuery4ENSEMBL constructs hypertext links to Ensembl using the provided ids. An additional 'species' argument must be passed to this function via the ... argument to htmlpage . The form of the argument must be e.g., species="Homosapiens" for human. Note the capitalized genus and underscore () separator.

getQueryLink directs calls to construct hypertext links using the provided ids.

getTDRows constructs each row of the resulting table.

getCells constructs each cell of the resulting table.

Note that some of these functions ( getQuery4OMIM , getQuery4UG , getQuery4FB ) attempt to return empty cells for ids that don't make sense, rather than broken links. For the other getQuery4XX functions, the end user must replace all nonsense ids with " " in order to have an empty cell.

Also note that creating additional links is quite simple. First, define a new 'getQuery4XX()' function modeled on the existing functions, then add this function to the getQueryLink function.

Value

Returns a vector of character strings representing the hypertext links.

Author

Jianhua Zhang jzhang@jimmy.harvard.edu with further modifications by James W. MacDonald jmacdon@med.umich.edu

Check for GO annotation

Description

Given a GO term, or a vector of GO terms and an ontology this function determines which of the terms have GO annotation in the specified ontology.

Usage

hasGOannote(x, which="MF")

Arguments

Details

The available GO annotation is searched and a determination of whether a specific GO identifier has a value in the specified ontology is made.

Value

A logical vector of the same length as x .

Seealso

get

Author

R. Gentleman

Examples

library("GO.db")
t1 <- "GO:0003680"
hasGOannote(t1)
hasGOannote(t1, "BP")

A dataset to show the human genome base pair locations per chromosome.

Description

The data is described above.

Format

A list, with the names consisting of the names of the chromosomes in the human genome (thus 24 elements). Each element consists of a named vector of +/- values - where each value represents the location of a base pair (the numeric value is the location, while the +/- denotes the strand value), with the name providing the name of the base pair.

Usage

data(hgByChroms)

Examples

data(hgByChroms)

A dataset which contains the lengths (in base pairs) of the human chromosomes.

Description

The data is described above.

Format

A vector containing 24 values, each corresponding to the total chromosome length.

Usage

data(hgCLengths)

Examples

data(hgCLengths)

chromLocation instance hgu95AProbLocs, an example of a chromLocation object

Description

gives chromosome locations for Affy U95 probes

Annotation data for the Affymetrix HGU95A GeneChip

Description

Data, in the form of environments for the Affymetrix U95A chip.

Format

These data sets provide environments with mappings from the Affymetrix identifiers to chromosomal location, in bases. The environments function like hashtables and can be accessed using mget . If the returned value is NA then the current mapping was unable to identify this. Mappings and data sources are constantly evolving so updating often is recommended.

Usage

data(hgu95Achroloc)

Examples

data(hgu95Achroloc)
data(sample.ExpressionSet)
mget(featureNames(sample.ExpressionSet)[330:340], env=hgu95Achroloc,
ifnotfound=NA)

Annotation data for the Affymetrix HGU95A GeneChip

Description

Data, in the form of environments for the Affymetrix U95A chip.

Format

This data set provides an environment (treat as a hashtable) with mappings from the Affymetrix identifiers to chromosome number/name. The environment functions like a hashtable and can be accessed using mget . If the returned value is NA then the current mapping was unable to identify this. Mappings and data sources are constantly evolving so updating often is recommended.

Usage

data(hgu95Achrom)

Examples

data(hgu95Achrom)
data(sample.ExpressionSet)
mget(featureNames(sample.ExpressionSet)[330:340], env=hgu95Achrom, ifnotfound=NA)

Annotation data for the Affymetrix HGU95A GeneChip

Description

Data, in the form of environments for the Affymetrix U95A chip.

Format

These data sets provide environments with mappings from the Affymetrix identifiers to Entrez Gene identifiers. The environment functions like a hashtable and can be accessed using mget . If the returned value is NA then the current mapping was unable to identify this. Mappings and data sources are constantly evolving so updating often is recommended.

Usage

data(hgu95All)

Examples

data(hgu95All)
data(sample.ExpressionSet)
mget(featureNames(sample.ExpressionSet)[330:340], env=hgu95All, ifnotfound=NA)

Annotation data for the Affymetrix HGU95A GeneChip

Description

Data, in the form of environments for the Affymetrix U95A chip.

Format

This data set provides an environment with mappings from the Affymetrix identifiers to gene symbol. The environment functions like a hashtables and can be accessed using mget . If the returned value is NA then the current mapping was unable to identify this. Mappings and data sources are constantly evolving so updating often is recommended.

Usage

data(hgu95Asym)

Examples

data(hgu95Asym)
data(sample.ExpressionSet)
mget(featureNames(sample.ExpressionSet)[330:340], env=hgu95Asym, ifnotfound=NA)

Class "homoData"

Description

A class to present data for HomologGene data of a matching sequence

Author

Jianhua Zhang

References

ftp://ftp.ncbi.nih.gov/pub/HomoloGene/README

Examples

new("homoData", homoPS = 82.3, homoLL = 2324853, homoOrg = "Homo sapins",
homoType = "B", homoURL = "", homoHGID = 12345)

Functions to build HTML pages

Description

This function is designed to create an HTML table containing both static information as well as links to various online annotation sources.

Usage

htmlpage(genelist, filename, title, othernames, table.head,
         table.center = TRUE, repository = list("en"), ...)

Arguments

Details

This function will accept a list or data.frame of character vectors, each containing different ids that are to be turned into hyperlinks (e.g., a list containing affy ids, genbank accession numbers, and Entrez Gene ids). For instances where there are more than one id per gene, use a sub-list of character vectors. See the vignette 'HowTo: Get HTML Output' for more information. Othernames should be a list or data.frame . Again, if there are multiple entries for a given gene, use a sub-list. This is more easily explained using an example - please see the examples section below and the above mentioned vignette.

In even the simplest case the genelist, othernames and repository have to be lists. A simple character vector will not suffice.

Note that this function now uses xtable to create the HTML table, and there is the ability to pass some arguments on to either xtable or print.xtable . One such argument would be 'append=TRUE', which would allow one to put lots of tables in one page, as long as the filename argument remained the same.

Additionally, the Ensembl repository needs a species argument in order to form a usable URI. This argument can be passed in the form of e.g., species = "Homosapiens". Note the capitalization of the genus, and the separation by an underscore ().

Value

This function is used only for the side effect of creating an HTML table.

Author

Robert Gentleman rgentlem@fhcrc.org, further modifications by James W. MacDonald jmacdon@med.umich.edu

Examples

## A very simple example. Two columns, one with links, the other without.

gos <- paste("GO:000000", 1:9, sep="")
notlinks <- LETTERS[1:9]

htmlpage(list(gos), "simple.html", "Two column data", list(notlinks),
c("GO IDs", "Letters"), repository = list("go"))

if(!interactive())
file.remove("simple.html")

## A more complex example with multiple links per cell
## first we create data to annotate
unigene <- list("Hs.600536",c("Hs.596913","HS.655491"),"Hs.76704")
refseq <- list(c("NM_001030050", "NM_001030047", "NM_001648",
"NM_001030049"), "NM_000860", c("NM_001011645", "NM_000044"))
entrez <- c("354", "3248", "367")
genelist <- list(unigene, refseq, entrez)

## now some other data

symb <- c("KLK3","HPGD","AR")
desc <- c("Prostate-specific antigen precursor",
"15-hydroxyprostaglandin dehydrogenase",
"Androgen receptor")
t.stat <- c(40.21, -22.14, 21.56)
p.value <- rep(0,3)
fold.change <- c(3.54, -2.35, 3.18)
expression <- matrix(c(11.78, 11.69, 11.62, 8.17, 5.78, 5.58, 5.68,
8.26, 9.08, 9.28, 9.19, 6.05), ncol=4, byrow=TRUE)

otherdata <- list(symb, desc, t.stat, p.value, fold.change, expression)
table.head <- c("UniGene", "RefSeq", "EntrezGene", "Symbol",
"Description", "t-stat", "p-value", "fold change",
paste("Sample", 1:4))

htmlpage(genelist, "test.html", "Some gene expression data", otherdata,
table.head, repository = list("ug","gb","en"))

if(!interactive())
file.remove("test.html")

Get or verify valid IDs for a package or OrgDb object.

Description

These functions either verify that a list of IDs are primary and valid IDs for a package, or else return all the valid primary IDs from a package

Usage

isValidKey(ids, pkg)
allValidKeys(pkg)
list(list("isValidKey"), list("character,character"))(ids, pkg)
list(list("isValidKey"), list("character,OrgDb"))(ids, pkg)
list(list("allValidKeys"), list("character"))(pkg)
list(list("allValidKeys"), list("OrgDb"))(pkg)

Arguments

Details

Every package has some kind of ID that is central to that package. For chip-based packages this will be some kind of probe, and for the organism based packages it will be something else (usually an entrez gene ID). isValidKey takes a list of IDs and tests to see whether or not they are present (valid) in a particular package. allValidKeys simply returns all the valid primary IDs for a package.

Value

isValidKey returns a vector of TRUE or FALSE values corresponding to whether or not the ID is valid.

allValidKeys returns a vector of all the valid primary IDs.

Seealso

updateSymbolsToValidKeys

Author

Marc Carlson

Examples

## 2 bad IDs and a 3rd that will be valid
ids <- c("15S_rRNA_2","21S_rRNA_4","15S_rRNA")
isValidKey(ids, "org.Sc.sgd")

## 2 good IDs and a 3rd that will not be valid
ids <- c("5600","7531", "altSymbol")
isValidKey(ids, "org.Hs.eg")

## Get all the valid primary id from org.Hs.eg.db
allValidKeys("org.Hs.eg")

A Function To Generate HTML Anchors

Description

This function will take a set of links and titles and will generate HTML anchor tags out of these values

Usage

makeAnchor(link, title, toMain = FALSE)

Arguments

Value

A vector of HTML anchor tags

Author

Jeff Gentry

Examples

makeAnchor("http://www.bioconductor.org","Bioconductor")

Functions to map to organism IDs used by NCBI homology.

Description

These functions help map to organism identifiers used at the NCBI.

Usage

mapOrgs(toMap, what = c("code","name"))
getOrgNameNCode()

Arguments

Details

mapOrgs converts organism codes to scientific names.

Value

mapOrgs returns a vector of character strings.

Author

Jianhua Zhang

References

ftp://ftp.ncbi.nih.gov/pub/HomoloGene/README

Convenience function for getting the organism from an object or package

Description

The most basic organism method just takes a character string (which represents a particular annotation package) and returns the organism that said package is based upon.

Usage

organism(object)

Arguments

Value

The name of the organism used for this package or object

Author

Marc Carlson

Examples

require(hgu95av2.db)
## get the organism for this annotation package
organism("hgu95av2")

## get the organism this object refers to
## (for a ChromLocation object)
z <- buildChromLocation("hgu95av2")
organism(z)

A function to map from probes to unique Entrez Gene IDs

Description

For any chip, this function computes the map from unique Entrez Gene ID to all probes.

Usage

p2LL(data)

Arguments

Details

This function is deprecated.

This is essentially the computation of the reverse map, we store probe to Entrez gene information in the ENTREZID environment. This is used to compute the inverse mapping.

Value

A list, with length equal to the number of unique Entrez Gene IDs on the chip, the elements correspond to the probes that map to the Gene ID.

Seealso

getEG

Author

R. Gentleman

Examples

library("hgu95av2.db")
x <- p2LL("hgu95av2")
table(sapply(x, length))

HTML Generation for PubMed Abstracts

Description

This function will take a pubMedAbst object, or a list of these objects and generate a web page that will list the titles of the abstracts and link to their full page on PubMed

Usage

pmAbst2HTML(absts, filename, title, frames = FALSE, table.center = TRUE)

Arguments

Details

This function uses the Entrez functionality provided by NCBI to retrieve the abstract URL at the PubMed site. It will then create a tabular webpage which will list the titles of the abstracts provided and have them link to the appropriate PubMed page. If frames is TRUE , the table of links will be on the left hand side of the page and the right hand will link directly to the appropriate PubMed page.

Value

If frames is FALSE , a simple HTML file is created with the name specified by filename .

If frames is TRUE , then there are four HTML files created, of the form XXXtop.html , XXXside.html , XXXmain.html and XXXindex.html , where XXX is the string provided by filename .

Seealso

pubMedAbst

Author

Jeff Gentry

Examples

x <- pubmed("9695952","8325638","8422497")
a <- xmlRoot(x)
numAbst <- length(xmlChildren(a))
absts <- list()
for (i in 1:numAbst) {
absts[[i]] <- buildPubMedAbst(a[[i]])
}
## First try it w/o frames - using a temporary
## file for the output
fname <- tempfile()
pmAbst2HTML(absts,filename=fname)

if (interactive())
browseURL(paste("file://",fname,sep=""))

## Now try it w/ frames, using temporary files again.
fnameBase <- tempfile()
pmAbst2HTML(absts,filename=fnameBase, frames=TRUE)

if (interactive())
browseURL(paste("file://",fnameBase,"index.html",sep=""))

An interface to grep for PubMed abstracts.

Description

A user friendly interface to the functionality provided by pubmed .

Usage

pm.abstGrep(pattern, absts, ...)

Arguments

Details

The absts are a list of PubMed XML objects that have been downloaded and parsed. This function lets the user quickly search the abstracts for any regular expression. The returned value is a logical vector indicating which of the abstracts contain the regular expression.

Value

The returned value is a logical vector indicating which of the abstracts contain the regular expression.

Seealso

pm.getabst , pm.titles

Author

Robert Gentleman

Examples

library("hgu95av2.db")
hoxa9 <- "37806_at"
absts <- pm.getabst(hoxa9, "hgu95av2")
pm.abstGrep("SH3", absts[[1]])
pm.abstGrep("autism", absts[[1]])

Obtain the abstracts for a set PubMed list.

Description

The data provided by PubMed is reduced to a small set. This set is then suitable for further rendering.

Usage

pm.getabst(geneids, basename)

Arguments

Details

We rely on the annotation in the package associated with the basename to provide PubMed identifiers for the genes described by the gene identifiers. With these in hand we then use the pmfetch utility to download the PubMed abstracts in XML form. These are then translated (transformed) to a shorter version containing a small subset of the data provided by PubMed.

This function has the side effect of creating an environment in .GlobalEnv that contains the mapping for the requested data. This is done for efficiency -- so we don't continually read in the data when there are many different queries to be performed.

Value

A list of lists containing objects of class pubMedAbst . There will be one element of the list for each identifier. Each of these elements is a list containing one abstract (of class pubMedAbst for each PubMed identifier associated with the gene identifier.

Seealso

pm.abstGrep , pm.titles

Author

Robert Gentleman

Examples

library("hgu95av2.db")
hoxa9 <- "37806_at"
absts <- pm.getabst(hoxa9, "hgu95av2")

use web to populate MIAME instance with pubmed details

Description

use web to populate MIAME instance with pubmed details

Usage

pmid2MIAME(pmid)

Arguments

Details

uses XML library to decode parts of the query response and load a MIAME object

Value

An instance of class MIAME

Author

Vince Carey stvjc@channing.harvard.edu

Examples

if (interactive()) pmid2MIAME("9843569")

A function to query PubMed

Description

Given a PMID, will create a URL which can be used to open a browser and retrieve the specified information from PubMed.

Usage

pmidQuery(query)

Arguments

Details

Using ublished details from NCBI we construct an appropriate string for directing a web browser to the information available at the NCBI.

Value

A character string containing the appropriate URL

Seealso

UniGeneQuery

Author

Jeff Gentry

References

NCBI, https://www.ncbi.nih.gov/

Examples

a <- "9695952"
pmidQuery(a)

Obtain the titles of the PubMed abstracts.

Description

This function returns the titles from a list of PubMed abstracts.

Usage

pm.titles(absts)

Arguments

Details

It simply uses sapply .

Value

A character vector of length equal to the number of abstracts. Each element is the title of the corresponding abstract.

Seealso

pm.abstGrep

Author

Robert Gentleman

Examples

library("hgu95av2.db")
hoxa9 <- "37806_at"
absts <- pm.getabst(hoxa9, "hgu95av2")
pm.titles(absts)[[1]][[1]]

Class pubMedAbst, a class to handle PubMed abstracts, and methods for processing them.

Description

This is a class representation for PubMed abstracts.

Seealso

pubmed , genbank

Author

Jeff Gentry

Examples

x <- pubmed("9695952","8325638","8422497")
a <- xmlRoot(x)
numAbst <- length(xmlChildren(a))
absts <- list()
for (i in 1:numAbst) {
absts[[i]] <- buildPubMedAbst(a[[i]])
}

A function to open the browser to Pubmed with the selected gene.

Description

Given a vector of Pubmed identifiers or accession numbers, the user can either have a browser display a URL showing a Pubmed query for those identifiers, or a XMLdoc object with the same data.

Usage

pubmed(...,disp=c("data","browser"), type=c("uid","accession"),
       pmaddress=.efetch("PubMed", disp, type))

Arguments

Details

A simple function to retrieve Pubmed data given a specific ID, either through XML or through a web browser. This function will accept either pubmed accession numbers or NCBI UIDs (defined as a Pubmed ID or a Medline ID) - although the types must not be mixed in a single call.

WARNING: The powers that be at NCBI have been known to ban the IP addresses of users who abuse their servers (currently defined as less then 2 seconds between queries). Do NOT put this function in a tight loop or you may find your access revoked.

Value

If the option "data" is used, an object of type XMLDoc is returned, unless there was an error with the query in which case an object of type try-error is returned.

If the option "browser" is used, nothing is returned.

Seealso

genbank , xmlTreeParse

Author

R. Gentleman

Examples

if( interactive() )
opts <- c("data","browser") else
opts <- "data"
for (dp in opts)
pubmed("11780146","11886385","11884611",disp=dp)

Function to extract data from the GEO web site

Description

Data files that are available at GEO web site are identified by GEO accession numbers. Given the url for the CGI script at GEO and a GEO accession number, the functions extract data from the web site and returns a matrix containing the data.

Usage

readGEOAnn(GEOAccNum, url = "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?")
readIDNAcc(GEOAccNum, url = "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?")
getGPLNames(url ="https://www.ncbi.nlm.nih.gov/geo/query/browse.cgi?") 
getSAGEFileInfo(url =
                       "https://www.ncbi.nlm.nih.gov/geo/query/browse.cgi?view=platforms&prtype=SAGE&dtype=SAGE")
getSAGEGPL(organism = "Homo sapiens", enzyme = c("NlaIII", "Sau3A"))
readUrl(url)

Arguments

Details

url is the CGI script that processes user's request. readGEOAnn invokes the CGI by passing a GEO accession number and then processes the data file obtained.

readIDNAcc calls readGEOAnn to read the data and the extracts the columns for probe ids and accession numbers. The GEOAccNum has to be the id for an Affymetrix chip.

getGPLNames parses the html file that lists GEO accession numbers and descriptions of the array represented by the corresponding GEO accession numbers.

Value

Both readGEOAnn and readIDNAcc return a matrix.

getGPLNames returns a named vector of the names of commercial arrays. The names of the vector are the corresponding GEO accession number.

Author

Jianhua Zhang

References

www.ncbi.nlm.nih.gov/geo

Examples

# Get array names and GEO accession numbers
#geoAccNums <- getGPLNames()
# Read the annotation data file for HG-U133A which is GPL96 based on
# examining geoAccNums
#temp <- readGEOAnn(GEOAccNum = "GPL96")
#temp2 <- readIDNAcc(GEOAccNum = "GPL96")

A Function To Serialize Environment

Description

This function will serialize an environment in R to an XML format stored in a compressed file.

Usage

serializeEnv(env, fname)
serializeDataPkgEnvs(pkgDir)

Arguments

Details

The environment is converted into an XML format and then outputted to a gzipped file (using gzfile ). The values in the environment are serialized (using serialize ) in ASCII format although the keys are stored in plain text.

The format of the XML is very simple, with the primary block being values , which contain blocks of entries , and each entry having a key and a value . For instance, if we had an environment with one value in it, the character c with a key of a (e.g. assign("a", "c", env=foo) ), this is what the output would look like.

list(" ", " <?xml version="1.0"?> ", " ", " ", " ", " a ", " ", " ", " A\n2\n131072\n66560\n1040\n1\n1033\n1\nc\n ", " ", "
", " ", " ")

Seealso

gzfile , serialize

Author

Jeff Gentry

Examples

z <- new.env()
assign("a", 1, env=z)
assign("b", 2, env=z)
assign("c", 3, env=z)
serializeEnv(z, tempfile())

Functions to add arbitrary repositories

Description

These functions allow end users to add arbitrary repositories for use with the htmlpage function.

Usage

setRepository(repository, FUN, ..., verbose=TRUE)
getRepositories()
clearRepository(repository, verbose=TRUE)

Arguments

Details

These functions allow end users to add, view, and remove repositories for use with the htmlpage function. getRepositories will output a vector of names for available repositories. clearRepository can be used to remove a repository if so desired. setRepository can be used to add a repository. See the examples section for the format of the FUN argument.

Once a new repository has been set, the htmlpage function can be called using the name of the new repository as a value in the repository argument (e.g., htmlpage(, repository = list("newrepositoryname"))

Author

Martin Morgan mtmorgan@fhcrc.org

Examples

## A simple fake URI
repofun <- function(ids, ...)
paste("http://www.afakeuri.com/", ids, sep = "")

setRepository("simple", repofun)

## More complicated, we want to make sure that
## NAs get converted to empty cells

repofun <- function(ids, ...){
bIDs <- which(is.na(ids))
out <- paste("http://www.afakeuri.com/", ids, sep = "")
out[bIDs] <- "&nbsp;"
out
}

setRepository("complex", repofun)

## More complicated URI where we need to pass more information
## An example is Ensembl, which requires a species as part of the URI
## Since htmlpage() has an '...' argument, we can pass arbitrary
## arguments to this function that will be passed down to our
## repfun. Here we assume the argument species="Homo_sapiens" has been
## included in the call to htmlpage().


repofun <- function(ids, ...){
if(!is.null(list(...)$species))
species <- list(...)$species
else
stop("To make links for Ensembl, you need to pass a 'species' argument.",
call. = FALSE)
out <- paste("http://www.ensembl.org/", species, "/Search/Summary?species=",
species, ";idx=;q=", ids, sep = "")
out
}

setRepository("species_arg", repofun)

Take a list of symbols and translate them into the best possible ID for a package.

Description

Given a list of gene symbols and a package, find a valid ID for that package. If there isn't a valid ID, then return the original symbol.

Usage

updateSymbolsToValidKeys(symbols, pkg)

Arguments

Details

This is a convenience function for getting from a possibly varied list of gene symbols mapped onto something that is a nice concrete ID such as an entrez gene ID. When such an ID cannot be found, the original symbol will come back to prevent the loss of any information.

Value

This function returns a vector of IDs corresponding to the symbols that were input. If the symbols don't have a valid ID, then they come back instead.

Seealso

isValidKey

Author

Marc Carlson

Examples

## one "bad" ID, one that can be mapped onto a valid ID, and a 3rd
## which already is a valid ID
syms <- c("15S_rRNA_2","21S_rRNA_4","15S_rRNA")
updateSymbolsToValidKeys(syms, "org.Sc.sgd")

## 3 symbols and a 4th that will NOT be valid
syms <- c("MAPK11","P38B","FLJ45465", "altSymbol")
updateSymbolsToValidKeys(syms, "org.Hs.eg")

A function to select used genes on a chromosome from an ExpressionSet.

Description

Given an instance of an ExpressionSet , a chromLocation object and the name of a chromosome this function returns all genes represented in the ExpressionSet on the specified chromosome.

Usage

usedChromGenes(eSet, chrom, specChrom)

Arguments

Value

Returns a vector of gene names that represent the genes from the ExpressionSet that are on the specified chromosome.

Author

Jeff Gentry

Examples

data(sample.ExpressionSet)
data(hgu95AProbLocs)
usedChromGenes(sample.ExpressionSet, "1", hgu95AProbLocs)