Title: | Software to enable the smooth interfacing of different database packages |
---|---|
Description: | The package enables a simple unified interface to several annotation packages each of which has its own schema by taking advantage of the fact that each of these packages implements a select methods. |
Authors: | Marc Carlson [aut], Martin Morgan [aut], Valerie Obenchain [aut], Aliyu Atiku Mustapha [ctb] (Converted 'OrganismDbi' vignette from Sweave to RMarkdown / HTML.), Bioconductor Package Maintainer [cre] |
Maintainer: | Bioconductor Package Maintainer <[email protected]> |
License: | Artistic-2.0 |
Version: | 1.49.0 |
Built: | 2024-11-29 08:02:21 UTC |
Source: | https://github.com/bioc/OrganismDbi |
The makeOrganismDbFromBiomart
function allows the user
to make a OrganismDb object from transcript annotations
available on a BioMart database. This object has all the benefits of
a TxDb, plus an associated OrgDb and GODb object.
makeOrganismDbFromBiomart(biomart="ENSEMBL_MART_ENSEMBL", dataset="hsapiens_gene_ensembl", transcript_ids=NULL, circ_seqs=NULL, filter="", id_prefix="ensembl_", host="https://www.ensembl.org", port, miRBaseBuild=NA, keytype = "ENSEMBL", orgdb = NA)
makeOrganismDbFromBiomart(biomart="ENSEMBL_MART_ENSEMBL", dataset="hsapiens_gene_ensembl", transcript_ids=NULL, circ_seqs=NULL, filter="", id_prefix="ensembl_", host="https://www.ensembl.org", port, miRBaseBuild=NA, keytype = "ENSEMBL", orgdb = NA)
biomart |
which BioMart database to use.
Get the list of all available BioMart databases with the
|
dataset |
which dataset from BioMart. For example:
|
transcript_ids |
optionally, only retrieve transcript annotation data for the specified set of transcript ids. If this is used, then the meta information displayed for the resulting TxDb object will say 'Full dataset: no'. Otherwise it will say 'Full dataset: yes'. This TxDb object will be embedded in the resulting OrganismDb object. |
circ_seqs |
a character vector to list out which chromosomes should be marked as circular. |
filter |
Additional filters to use in the BioMart query. Must be
a named list. An example is |
host |
The host URL of the BioMart. Defaults to www.ensembl.org. |
port |
Deprecated: The port to use in the HTTP communication with the host. |
id_prefix |
Specifies the prefix used in BioMart attributes. For
example, some BioMarts may have an attribute specified as
|
miRBaseBuild |
specify the string for the appropriate build
Information from mirbase.db to use for microRNAs. This can be
learned by calling |
keytype |
This indicates the kind of key that this database will use as a foreign key between it's TxDb object and it's OrgDb object. So basically whatever the column name is for the foreign key from your OrgDb that your TxDb will need to map it's GENEID on to. By default it is "ENSEMBL" since the GENEID's for most biomaRt based TxDbs will be ensembl gene ids and therefore they will need to map to ENSEMBL gene mappings from the associated OrgDb object. |
orgdb |
By default, |
makeOrganismDbFromBiomart
is a convenience function that feeds
data from a BioMart database to the lower level
OrganismDb
constructor.
See ?makeOrganismDbFromUCSC
for a similar function
that feeds data from the UCSC source.
The listMarts
function from the biomaRt package can be
used to list all public BioMart databases.
Not all databases returned by this function contain datasets that
are compatible with (i.e. understood by) makeOrganismDbFromBiomart
.
Here is a list of datasets known to be compatible (updated on Sep 24, 2014):
All the datasets in the main Ensembl database:
use biomart="ensembl"
.
All the datasets in the Ensembl Fungi database:
use biomart="fungi_mart_XX"
where XX is the release
version of the database e.g. "fungi_mart_22"
.
All the datasets in the Ensembl Metazoa database:
use biomart="metazoa_mart_XX"
where XX is the release
version of the database e.g. "metazoa_mart_22"
.
All the datasets in the Ensembl Plants database:
use biomart="plants_mart_XX"
where XX is the release
version of the database e.g. "plants_mart_22"
.
All the datasets in the Ensembl Protists database:
use biomart="protists_mart_XX"
where XX is the release
version of the database e.g. "protists_mart_22"
.
All the datasets in the Gramene Mart:
use biomart="ENSEMBL_MART_PLANT"
.
Not all these datasets have CDS information.
A OrganismDb object.
M. Carlson
makeOrganismDbFromUCSC
for convenient ways to make a
OrganismDb object from UCSC online resources.
The listMarts
, useMart
,
and listDatasets
functions in the
biomaRt package.
The supportedMiRBaseBuildValues
function for
listing all the possible values for the miRBaseBuild
argument.
The OrganismDb class.
## Discover which datasets are available in the "ensembl" BioMart ## database: library(biomaRt) mart <- useEnsembl("ensembl") datasets <- listDatasets(mart) head(datasets) ## Retrieving an incomplete transcript dataset for Human from the ## "ensembl" BioMart database: transcript_ids <- c( "ENST00000013894", "ENST00000268655", "ENST00000313243", "ENST00000435657", "ENST00000384428", "ENST00000478783" ) odb <- makeOrganismDbFromBiomart(transcript_ids=transcript_ids) odb # note that these annotations match the GRCh38 genome assembly if (interactive()) { ## Now what if we want to use another mirror? We might make use of the ## new host argument. But wait! If we use biomaRt, we can see that ## this host has named the mart differently! listMarts(host="https://useast.ensembl.org") ## Therefore we must also change the name passed into the "mart" ## argument thusly: makeOrganismDbFromBiomart( biomart="ENSEMBL_MART_ENSEMBL", transcript_ids=transcript_ids, host="https://useast.ensembl.org" ) }
## Discover which datasets are available in the "ensembl" BioMart ## database: library(biomaRt) mart <- useEnsembl("ensembl") datasets <- listDatasets(mart) head(datasets) ## Retrieving an incomplete transcript dataset for Human from the ## "ensembl" BioMart database: transcript_ids <- c( "ENST00000013894", "ENST00000268655", "ENST00000313243", "ENST00000435657", "ENST00000384428", "ENST00000478783" ) odb <- makeOrganismDbFromBiomart(transcript_ids=transcript_ids) odb # note that these annotations match the GRCh38 genome assembly if (interactive()) { ## Now what if we want to use another mirror? We might make use of the ## new host argument. But wait! If we use biomaRt, we can see that ## this host has named the mart differently! listMarts(host="https://useast.ensembl.org") ## Therefore we must also change the name passed into the "mart" ## argument thusly: makeOrganismDbFromBiomart( biomart="ENSEMBL_MART_ENSEMBL", transcript_ids=transcript_ids, host="https://useast.ensembl.org" ) }
The makeOrganismDbFromTxDb
function allows the user
to make a OrganismDb object from an existing TxDb object.
makeOrganismDbFromTxDb(txdb, keytype=NA, orgdb=NA)
makeOrganismDbFromTxDb(txdb, keytype=NA, orgdb=NA)
txdb |
a |
.
keytype |
By default, |
.
orgdb |
By default, |
makeOrganismDbFromTxDb
is a convenience function that processes
a TxDb
object and pairs it up with GO.db and an appropriate
OrgDb
object to make a OrganismDb
object.
See ?makeOrganismDbFromBiomart
and
?makeOrganismDbFromUCSC
for a similar function that
feeds data from either a BioMart or UCSC.
A OrganismDb object.
M. Carlson
makeOrganismDbFromBiomart
for convenient ways to make a
OrganismDb object from BioMart online resources.
The OrganismDb class.
## Not run: ## lets start with a txdb object transcript_ids <- c( "uc009uzf.1", "uc009uzg.1", "uc009uzh.1", "uc009uzi.1", "uc009uzj.1" ) txdbMouse <- makeTxDbFromUCSC(genome="mm9", tablename="knownGene", transcript_ids=transcript_ids) ## Using that, we can call our function to promote it to an OrgDb object: odb <- makeOrganismDbFromTxDb(txdb=txdbMouse) columns(odb) ## End(Not run)
## Not run: ## lets start with a txdb object transcript_ids <- c( "uc009uzf.1", "uc009uzg.1", "uc009uzh.1", "uc009uzi.1", "uc009uzj.1" ) txdbMouse <- makeTxDbFromUCSC(genome="mm9", tablename="knownGene", transcript_ids=transcript_ids) ## Using that, we can call our function to promote it to an OrgDb object: odb <- makeOrganismDbFromTxDb(txdb=txdbMouse) columns(odb) ## End(Not run)
The makeOrganismDbFromUCSC
function allows the user
to make a OrganismDb object from transcript annotations
available at the UCSC Genome Browser.
makeOrganismDbFromUCSC( genome="hg19", tablename="knownGene", transcript_ids=NULL, circ_seqs=NULL, url="http://genome.ucsc.edu/cgi-bin/", goldenPath.url=getOption("UCSC.goldenPath.url"), miRBaseBuild=NA)
makeOrganismDbFromUCSC( genome="hg19", tablename="knownGene", transcript_ids=NULL, circ_seqs=NULL, url="http://genome.ucsc.edu/cgi-bin/", goldenPath.url=getOption("UCSC.goldenPath.url"), miRBaseBuild=NA)
genome |
genome abbreviation used by UCSC and obtained by
|
tablename |
name of the UCSC table containing the transcript
annotations to retrieve. Use the |
transcript_ids |
optionally, only retrieve transcript annotation data for the specified set of transcript ids. If this is used, then the meta information displayed for the resulting OrganismDb object will say 'Full dataset: no'. Otherwise it will say 'Full dataset: yes'. |
circ_seqs |
a character vector to list out which chromosomes should be marked as circular. |
url |
Deprecated (will be ignored). |
goldenPath.url |
use to specify the location of an alternate UCSC Genome Browser. |
miRBaseBuild |
specify the string for the appropriate build
Information from mirbase.db to use for microRNAs. This can be
learned by calling |
makeOrganismDbFromUCSC
is a convenience function that feeds
data from the UCSC source to the lower level OrganismDb
function.
See ?makeOrganismDbFromBiomart
for a similar function
that feeds data from a BioMart database.
A OrganismDb object.
M. Carlson
makeOrganismDbFromBiomart
for convenient ways to make a
OrganismDb object from BioMart online resources.
ucscGenomes
in the rtracklayer
package.
The supportedMiRBaseBuildValues
function for
listing all the possible values for the miRBaseBuild
argument.
The OrganismDb class.
## Not run: ## Display the list of genomes available at UCSC: library(rtracklayer) library(RMariaDB) ucscGenomes()[ , "db"] ## Display the list of tables supported by makeOrganismDbFromUCSC(): supportedUCSCtables() \dontrun{ ## Retrieving a full transcript dataset for Yeast from UCSC: odb1 <- makeOrganismDbFromUCSC(genome="sacCer2", tablename="ensGene") } ## Retrieving an incomplete transcript dataset for Mouse from UCSC ## (only transcripts linked to Entrez Gene ID 22290): transcript_ids <- c( "uc009uzf.1", "uc009uzg.1", "uc009uzh.1", "uc009uzi.1", "uc009uzj.1" ) odb2 <- makeOrganismDbFromUCSC(genome="mm9", tablename="knownGene", transcript_ids=transcript_ids) odb2 ## End(Not run)
## Not run: ## Display the list of genomes available at UCSC: library(rtracklayer) library(RMariaDB) ucscGenomes()[ , "db"] ## Display the list of tables supported by makeOrganismDbFromUCSC(): supportedUCSCtables() \dontrun{ ## Retrieving a full transcript dataset for Yeast from UCSC: odb1 <- makeOrganismDbFromUCSC(genome="sacCer2", tablename="ensGene") } ## Retrieving an incomplete transcript dataset for Mouse from UCSC ## (only transcripts linked to Entrez Gene ID 22290): transcript_ids <- c( "uc009uzf.1", "uc009uzg.1", "uc009uzh.1", "uc009uzi.1", "uc009uzj.1" ) odb2 <- makeOrganismDbFromUCSC(genome="mm9", tablename="knownGene", transcript_ids=transcript_ids) odb2 ## End(Not run)
makeOrganismPackage
is a method that generates a package
that will load an appropriate annotationOrganismDb
object that
will in turn point to existing annotation packages.
makeOrganismPackage (pkgname, graphData, organism, version, maintainer, author, destDir, license="Artistic-2.0")
makeOrganismPackage (pkgname, graphData, organism, version, maintainer, author, destDir, license="Artistic-2.0")
pkgname |
What is the desired package name. Traditionally, this should be the genus and species separated by a ".". So as an example, "Homo.sapiens" would be the package name for human |
graphData |
A list of short character vectors. Each character vector in the list is exactly two elements long and represents a join relationship between two packages. The names of these character vectors are the package names and the values are the foreign keys that should be used to connect each package. All foreign keys must be values that can be returned by the columns method for each package in question, and obviously they also must be the same kind of identifier as well. |
organism |
The name of the organism this package represents |
version |
What is the version number for this package? |
maintainer |
Who is the package maintainer? (must include email to be valid) |
author |
Who is the creator of this package? |
destDir |
A path where the package source should be assembled. |
license |
What is the license (and it's version) |
The purpose of this method is to create a special package that will
depend on existing annotation packages and which will load a special
annotationOrganismDb
object that will allow proper dispatch of
special select methods. These methods will allow the user to easily
query across multiple annotation resources via information contained
by the annotationOrganismDb
object. Because the end result will
be a package that treats all the data mapped together as a single
source, the user is encouraged to take extra care to ensure that the
different packages used are from the same build etc.
A special package to load an OrganismDb object.
M. Carlson
## set up the list with the relevant relationships: gd <- list(join1 = c(GO.db="GOID", org.Hs.eg.db="GO"), join2 = c(org.Hs.eg.db="ENTREZID", TxDb.Hsapiens.UCSC.hg19.knownGene="GENEID")) ## sets up a temporary directory for this example ## (users won't need to do this step) destination <- tempfile() dir.create(destination) ## makes an Organism package for human called Homo.sapiens if(interactive()){ makeOrganismPackage(pkgname = "Homo.sapiens", graphData = gd, organism = "Homo sapiens", version = "1.0.0", maintainer = "Bioconductor Package Maintainer <[email protected]>", author = "Bioconductor Core Team", destDir = destination, license = "Artistic-2.0") }
## set up the list with the relevant relationships: gd <- list(join1 = c(GO.db="GOID", org.Hs.eg.db="GO"), join2 = c(org.Hs.eg.db="ENTREZID", TxDb.Hsapiens.UCSC.hg19.knownGene="GENEID")) ## sets up a temporary directory for this example ## (users won't need to do this step) destination <- tempfile() dir.create(destination) ## makes an Organism package for human called Homo.sapiens if(interactive()){ makeOrganismPackage(pkgname = "Homo.sapiens", graphData = gd, organism = "Homo sapiens", version = "1.0.0", maintainer = "Bioconductor Package Maintainer <[email protected]>", author = "Bioconductor Core Team", destDir = destination, license = "Artistic-2.0") }
Map range coordinates between features in the transcriptome and genome (reference) space.
See mapToAlignments
in the GenomicAlignments package
for mapping coordinates between reads (local) and genome (reference)
space using a CIGAR alignment.
## S4 method for signature 'ANY,MultiDb' mapToTranscripts(x, transcripts, ignore.strand = TRUE, extractor.fun = GenomicFeatures::transcripts, ...)
## S4 method for signature 'ANY,MultiDb' mapToTranscripts(x, transcripts, ignore.strand = TRUE, extractor.fun = GenomicFeatures::transcripts, ...)
x |
|
transcripts |
The |
ignore.strand |
When TRUE, strand is ignored in overlap operations. |
extractor.fun |
Function to extract genomic features from a Valid
|
... |
Additional arguments passed to |
mapToTranscripts
The genomic range in x
is mapped to the local position in the
transcripts
ranges. A successful mapping occurs when x
is completely within the transcripts
range, equivalent to:
findOverlaps(..., type="within")
Transcriptome-based coordinates start counting at 1 at the beginning
of the transcripts
range and return positions where x
was aligned. The seqlevels of the return object are taken from the
transcripts
object and should be transcript names. In this
direction, mapping is attempted between all elements of x
and
all elements of transcripts
.
An object the same class as x
.
Parallel methods return an object the same shape as x
. Ranges that
cannot be mapped (out of bounds or strand mismatch) are returned as
zero-width ranges starting at 0 with a seqname of "UNMAPPED".
Non-parallel methods return an object that varies in length similar to a
Hits object. The result only contains mapped records, strand mismatch
and out of bound ranges are not returned. xHits
and
transcriptsHits
metadata columns indicate the elements of x
and transcripts
used in the mapping.
When present, names from x
are propagated to the output. When
mapping to transcript coordinates, seqlevels of the output are the names
on the transcripts
object; most often these will be transcript
names. When mapping to the genome, seqlevels of the output are the seqlevels
of transcripts
which are usually chromosome names.
V. Obenchain, M. Lawrence and H. Pagès; ported to work with OrganismDbi by Marc Carlson
## --------------------------------------------------------------------- ## A. Basic Use ## --------------------------------------------------------------------- library(Homo.sapiens) x <- GRanges("chr5", IRanges(c(173315331,174151575), width=400, names=LETTERS[1:2])) ## Map to transcript coordinates: mapToTranscripts(x, Homo.sapiens)
## --------------------------------------------------------------------- ## A. Basic Use ## --------------------------------------------------------------------- library(Homo.sapiens) x <- GRanges("chr5", IRanges(c(173315331,174151575), width=400, names=LETTERS[1:2])) ## Map to transcript coordinates: mapToTranscripts(x, Homo.sapiens)
The OrganismDb class is a container for storing knowledge about existing Annotation packages and the relationships between these resources. The purpose of this object and it's associated methods is to provide a means by which users can conveniently query for data from several different annotation resources at the same time using a familiar interface.
The supporting methods select
, columns
and keys
are
used together to extract data from an OrganismDb
object in a manner that should be consistent with how these are used
on the supporting annotation resources.
The family of seqinfo
style getters (seqinfo
,
seqlevels
, seqlengths
, isCircular
, genome
,
and seqnameStyle
) is also supported for OrganismDb objects
provided that the object in question has an embedded TxDb
object.
In the code snippets below, x
is a OrganismDb object.
keytypes(x)
:allows the user to discover which keytypes can be passed in to
select
or keys
and the keytype
argument.
keys(x, keytype, pattern, column, fuzzy)
:Return keys for the database contained in the TxDb object .
The keytype
argument specifies the kind of keys that will
be returned and is always required.
If keys
is used with pattern
, it will pattern match
on the keytype
.
But if the column
argument is also provided along with the
pattern
argument, then pattern
will be matched
against the values in column
instead.
If keys
is called with column
and no pattern
argument, then it will return all keys that have corresponding
values in the column
argument.
Thus, the behavior of keys
all depends on how many arguments are
specified.
Use of the fuzzy
argument will toggle fuzzy matching to
TRUE or FALSE. If pattern
is not used, fuzzy is ignored.
columns(x)
:shows which kinds of data can be returned for the
OrganismDb
object.
select(x, keys, columns, keytype)
:When all the appropriate arguments are specifiedm select
will retrieve the matching data as a data.frame based on
parameters for selected keys
and columns
and
keytype
arguments.
mapIds(x, keys, columns, keytype, ..., multiVals)
:When all the appropriate arguments are specifiedm mapIds
will retrieve the matching data as a vector or list based on
parameters for selected keys
and columns
and
keytype
arguments. The multiVals argument can be used to
choose the format of the values returned. Possible values for
multiVals are:
This value means that when there are multiple matches only the 1st thing that comes back will be returned. This is the default behavior
This will just returns a list object to the end user
This will remove all elements that contain multiple matches and will therefore return a shorter vector than what came in whenever some of the keys match more than one value
This will return an NA value whenever there are multiple matches
This just returns a SimpleCharacterList object
You can also supply a function to the multiVals
argument for custom behaviors. The function must take a single argument and return a single value. This function will be applied to all the elements and will serve a 'rule' that for which thing to keep when there is more than one element. So for example this example function will always grab the last element in each result: last <- function(x){x[[length(x)]]}
selectByRanges(x, ranges, columns, overlaps,
ignore.strand)
: When all the appropriate arguments are specified,
selectByRanges
will return an annotated GRanges object that
has been generated based on what you passed in to the ranges
argument and whether that overlapped with what you specified in
the overlaps argument. Internally this function will get
annotation features and overlaps by calling the appropriate
annotation methods indicated by the overlaps argument. The value
for overlaps can be any of: gene, tx, exons, cds, 5utr, introns or
3utr. The default value is 'tx' which will return to you, your
annotated ranges based on whether the overlapped with the
transcript ranges of any gene in the associated TxDb object based
on the gene models it contains. Also: the number of ranges
returned to you will match the number of genes that your ranges
argument overlapped for the type of overlap that you specified.
So if some of your ranges are large and overlap several features
then you will get many duplicated ranges returned with one for
each gene that has an overlapping feature. The columns values
that you request will be returned in the mcols for the annotated
GRanges object that is the return value for this function.
Finally, the ignore.strand argument is provided to indicate
whether or not findOverlaps should ignore or respect the strand.
selectRangesById(x, keys, columns, keytype, feature)
: When
all the appropriate arguments are specified,
selectRangesById
will return a GRangesList object that
correspond to gene models GRanges for the keys that you specify
with the keys and keytype arguments. The annotation ranges
retrieved for this will be specified by the feature argument and
can be: gene, tx, exon or cds. The default is 'tx' which will
return the transcript ranges for each gene as a GRanges object in
the list. Extra data can also be returned in the mcols values for
those GRanges by using the columns argument.
resources(x)
: shows where the db files are for resources
that are used to store the data for the OrganismDb
object.
TxDb(x)
: Accessor for the TxDb object of a
OrganismDb
object.
TxDb(x) <- value
: Allows you to swap in an alternative TxDb
for a given OrganismDb
object. This is most often useful
when combined with saveDb(TxDb, file)
, which returns the
saved TxDb, so that you can save a TxDb to disc and then assign
the saved version right into your OrganismDb
object.
Marc Carlson
AnnotationDb-class for more descriptsion
of methods select
,keytypes
,keys
and columns
.
makeOrganismPackage for functions
used to generate an OrganismDb
based package.
rangeBasedAccessors for the range based methods
used in extracting data from a OrganismDb
object.
Topics in the GenomeInfoDb
package:
seqinfo
seqlevels
seqlengths
isCircular
genome
## load a package that creates an OrganismDb library(Homo.sapiens) ls(2) ## then the methods can be used on this object. columns <- columns(Homo.sapiens)[c(7,10,11,12)] keys <- head(keys(org.Hs.eg.db, "ENTREZID")) keytype <- "ENTREZID" res <- select(Homo.sapiens, keys, columns, keytype) head(res) res <- mapIds(Homo.sapiens, keys=c('1','10'), column='ALIAS', keytype='ENTREZID', multiVals="CharacterList") ## get symbols for ranges in question: ranges <- GRanges(seqnames=Rle(c('chr11'), c(2)), IRanges(start=c(107899550, 108025550), end=c(108291889, 108050000)), strand='*', seqinfo=seqinfo(Homo.sapiens)) selectByRanges(Homo.sapiens, ranges, 'SYMBOL') ## Or extract the gene model for the 'A1BG' gene: selectRangesById(Homo.sapiens, 'A1BG', keytype='SYMBOL') ## Get the DB connections or DB file paths associated with those for ## each. dbconn(Homo.sapiens) dbfile(Homo.sapiens) ## extract the taxonomyId taxonomyId(Homo.sapiens) ##extract the resources resources(Homo.sapiens)
## load a package that creates an OrganismDb library(Homo.sapiens) ls(2) ## then the methods can be used on this object. columns <- columns(Homo.sapiens)[c(7,10,11,12)] keys <- head(keys(org.Hs.eg.db, "ENTREZID")) keytype <- "ENTREZID" res <- select(Homo.sapiens, keys, columns, keytype) head(res) res <- mapIds(Homo.sapiens, keys=c('1','10'), column='ALIAS', keytype='ENTREZID', multiVals="CharacterList") ## get symbols for ranges in question: ranges <- GRanges(seqnames=Rle(c('chr11'), c(2)), IRanges(start=c(107899550, 108025550), end=c(108291889, 108050000)), strand='*', seqinfo=seqinfo(Homo.sapiens)) selectByRanges(Homo.sapiens, ranges, 'SYMBOL') ## Or extract the gene model for the 'A1BG' gene: selectRangesById(Homo.sapiens, 'A1BG', keytype='SYMBOL') ## Get the DB connections or DB file paths associated with those for ## each. dbconn(Homo.sapiens) dbfile(Homo.sapiens) ## extract the taxonomyId taxonomyId(Homo.sapiens) ##extract the resources resources(Homo.sapiens)
Generic functions to extract genomic features from an object. This page documents the methods for OrganismDb objects only.
## S4 method for signature 'MultiDb' transcripts(x, columns=c("TXID", "TXNAME"), filter=NULL) ## S4 method for signature 'MultiDb' exons(x, columns="EXONID", filter=NULL) ## S4 method for signature 'MultiDb' cds(x, columns="CDSID", filter=NULL) ## S4 method for signature 'MultiDb' genes(x, columns="GENEID", filter=NULL) ## S4 method for signature 'MultiDb' transcriptsBy(x, by, columns, use.names=FALSE, outerMcols=FALSE) ## S4 method for signature 'MultiDb' exonsBy(x, by, columns, use.names=FALSE, outerMcols=FALSE) ## S4 method for signature 'MultiDb' cdsBy(x, by, columns, use.names=FALSE, outerMcols=FALSE) ## S4 method for signature 'MultiDb' getTxDbIfAvailable(x, ...) ## S4 method for signature 'MultiDb' asBED(x) ## S4 method for signature 'MultiDb' asGFF(x) ## S4 method for signature 'MultiDb' microRNAs(x) ## S4 method for signature 'MultiDb' tRNAs(x) ## S4 method for signature 'MultiDb' promoters(x, upstream=2000, downstream=200, use.names=TRUE, ...) ## S4 method for signature 'GenomicRanges,MultiDb' distance(x, y, ignore.strand=FALSE, ..., id, type=c("gene", "tx", "exon", "cds")) ## S4 method for signature 'BSgenome' extractTranscriptSeqs(x, transcripts, strand = "+") ## S4 method for signature 'MultiDb' extractUpstreamSeqs(x, genes, width=1000, exclude.seqlevels=NULL) ## S4 method for signature 'MultiDb' intronsByTranscript(x, use.names=FALSE) ## S4 method for signature 'MultiDb' fiveUTRsByTranscript(x, use.names=FALSE) ## S4 method for signature 'MultiDb' threeUTRsByTranscript(x, use.names=FALSE) ## S4 method for signature 'MultiDb' isActiveSeq(x)
## S4 method for signature 'MultiDb' transcripts(x, columns=c("TXID", "TXNAME"), filter=NULL) ## S4 method for signature 'MultiDb' exons(x, columns="EXONID", filter=NULL) ## S4 method for signature 'MultiDb' cds(x, columns="CDSID", filter=NULL) ## S4 method for signature 'MultiDb' genes(x, columns="GENEID", filter=NULL) ## S4 method for signature 'MultiDb' transcriptsBy(x, by, columns, use.names=FALSE, outerMcols=FALSE) ## S4 method for signature 'MultiDb' exonsBy(x, by, columns, use.names=FALSE, outerMcols=FALSE) ## S4 method for signature 'MultiDb' cdsBy(x, by, columns, use.names=FALSE, outerMcols=FALSE) ## S4 method for signature 'MultiDb' getTxDbIfAvailable(x, ...) ## S4 method for signature 'MultiDb' asBED(x) ## S4 method for signature 'MultiDb' asGFF(x) ## S4 method for signature 'MultiDb' microRNAs(x) ## S4 method for signature 'MultiDb' tRNAs(x) ## S4 method for signature 'MultiDb' promoters(x, upstream=2000, downstream=200, use.names=TRUE, ...) ## S4 method for signature 'GenomicRanges,MultiDb' distance(x, y, ignore.strand=FALSE, ..., id, type=c("gene", "tx", "exon", "cds")) ## S4 method for signature 'BSgenome' extractTranscriptSeqs(x, transcripts, strand = "+") ## S4 method for signature 'MultiDb' extractUpstreamSeqs(x, genes, width=1000, exclude.seqlevels=NULL) ## S4 method for signature 'MultiDb' intronsByTranscript(x, use.names=FALSE) ## S4 method for signature 'MultiDb' fiveUTRsByTranscript(x, use.names=FALSE) ## S4 method for signature 'MultiDb' threeUTRsByTranscript(x, use.names=FALSE) ## S4 method for signature 'MultiDb' isActiveSeq(x)
x |
A MultiDb object, except in the extractTranscriptSeqs
method where it is a |
... |
Arguments to be passed to or from methods. |
by |
One of |
columns |
The columns or kinds of metadata that can be retrieved from the
database. All possible columns are returned by using the |
filter |
Either |
use.names |
Controls how to set the names of the returned
GRangesList object.
These functions return all the features of a given type (e.g.
all the exons) grouped by another feature type (e.g. grouped by
transcript) in a GRangesList object.
By default (i.e. if Finally, |
upstream |
For |
downstream |
For |
y |
For |
id |
A |
type |
A |
ignore.strand |
A |
outerMcols |
A |
transcripts |
An object representing the exon ranges of each transcript to extract.
It must be a GRangesList or MultiDb
object while the |
strand |
Only supported when Can be an atomic vector, a factor, or an Rle object,
in which case it indicates the strand of each transcript (i.e. all the
exons in a transcript are considered to be on the same strand).
More precisely: it's turned into a factor (or factor-Rle)
that has the "standard strand levels" (this is done by calling the
|
genes |
An object containing the locations (i.e. chromosome name, start, end, and
strand) of the genes or transcripts with respect to the reference genome.
Only GenomicRanges and MultiDb objects
are supported at the moment. If the latter, the gene locations are obtained
by calling the |
width |
How many bases to extract upstream of each TSS (transcription start site). |
exclude.seqlevels |
A character vector containing the chromosome names (a.k.a. sequence levels) to exclude when the genes are obtained from a MultiDb object. |
These are the range based functions for extracting transcript information from a MultiDb object.
a GRanges or GRangesList object
M. Carlson
MultiDb-class for how to use the
simple "select" interface to extract information from a
MultiDb
object.
transcripts for the original
transcripts
method and related methods.
transcriptsBy for the original
transcriptsBy
method and related methods.
## extracting all transcripts from Homo.sapiens with some extra metadata library(Homo.sapiens) cols = c("TXNAME","SYMBOL") res <- transcripts(Homo.sapiens, columns=cols) ## extracting all transcripts from Homo.sapiens, grouped by gene and ## with extra metadata res <- transcriptsBy(Homo.sapiens, by="gene", columns=cols) ## list possible values for columns argument: columns(Homo.sapiens) ## Get the TxDb from an MultiDb object (if it's available) getTxDbIfAvailable(Homo.sapiens) ## Other functions listed above should work in way similar to their TxDb ## counterparts. So for example: promoters(Homo.sapiens) ## Should give the same value as: promoters(getTxDbIfAvailable(Homo.sapiens))
## extracting all transcripts from Homo.sapiens with some extra metadata library(Homo.sapiens) cols = c("TXNAME","SYMBOL") res <- transcripts(Homo.sapiens, columns=cols) ## extracting all transcripts from Homo.sapiens, grouped by gene and ## with extra metadata res <- transcriptsBy(Homo.sapiens, by="gene", columns=cols) ## list possible values for columns argument: columns(Homo.sapiens) ## Get the TxDb from an MultiDb object (if it's available) getTxDbIfAvailable(Homo.sapiens) ## Other functions listed above should work in way similar to their TxDb ## counterparts. So for example: promoters(Homo.sapiens) ## Should give the same value as: promoters(getTxDbIfAvailable(Homo.sapiens))