R/allEndpoints.R
get_platforms_by_ids.Rd
Retrieve all platforms matching a set of platform identifiers
get_platforms_by_ids(
platforms = NA_character_,
filter = NA_character_,
taxa = NA_character_,
offset = 0L,
limit = 20L,
sort = "+id",
raw = getOption("gemma.raw", FALSE),
memoised = getOption("gemma.memoised", FALSE),
file = getOption("gemma.file", NA_character_),
overwrite = getOption("gemma.overwrite", FALSE)
)
Platform numerical identifiers or platform short names. If not specified, all platforms will be returned instead
Filter results by matching expression. Use filter_properties
function to get a list of all available parameters. These properties can be
combined using "and" "or" clauses and may contain common operators such as "=", "<" or "in".
(e.g. "taxon.commonName = human", "taxon.commonName in (human,mouse), "id < 1000")
A vector of taxon common names (e.g. human, mouse, rat). Providing multiple
species will return results for all species. These are appended
to the filter and equivalent to filtering for taxon.commonName
property
The offset of the first retrieved result.
Defaults to 20. Limits the result to specified amount
of objects. Has a maximum value of 100. Use together with offset
and
the totalElements
attribute in the output to
compile all data if needed.
Order results by the given property and direction. The '+' sign indicate ascending order whereas the '-' indicate descending.
TRUE
to receive results as-is from Gemma, or FALSE
to enable
parsing. Raw results usually contain additional fields and flags that are
omitted in the parsed results.
Whether or not to save to cache for future calls with the
same inputs and use the result saved in cache if a result is already saved.
Doing options(gemma.memoised = TRUE)
will ensure that the cache is always
used. Use forget_gemma_memoised
to clear the cache.
The name of a file to save the results to, or NULL
to not write
results to a file. If raw == TRUE
, the output will be the raw endpoint from the
API, likely a JSON or a gzip file. Otherwise, it will be a RDS file.
Whether or not to overwrite if a file exists at the specified filename.
A data table with information about the platform(s). A list if raw = TRUE
. A 404 error
if the given identifier
does not map to any object
The fields of the output data.table are:
platform.ID
: Internal identifier of the platform
platform.shortName
: Shortname of the platform.
platform.name
: Full name of the platform.
platform.description
: Free text description of the platform
platform.troubled
: Whether or not the platform was marked "troubled" by a Gemma process or a curator
platform.experimentCount
: Number of experiments using the platform within Gemma
platform.type
: Technology type for the platform.
taxon.name
: Name of the species platform was made for
taxon.scientific
: Scientific name for the taxon
taxon.ID
: Internal identifier given to the species by Gemma
taxon.NCBI
: NCBI ID of the taxon
taxon.database.name
: Underlying database used in Gemma for the taxon
taxon.database.ID
: ID of the underyling database used in Gemma for the taxon
get_platforms_by_ids("GPL1355")
#> platform.ID platform.shortName platform.name
#> <int> <char> <char>
#> 1: 2 GPL1355 Affymetrix GeneChip Rat Genome 230 2.0 Array
#> platform.description
#> <char>
#> 1: The GeneChip Rat Genome 230 2.0 Array is a powerful tool for toxicology, neurobiology, and other applications using rat as a model organism. - Provides comprehensive coverage of the transcribed rat genome on a single array - Comprised of more than 31,000 probe sets, analyzing over 30,000 transcripts and variants from over 28,000 well-substantiated rat genes - The publicly available draft of the rat genome and leading public rat databases were used to refine sequences and provide a higher quality of data output All probe sets represented on the GeneChip Rat Expression Set 230 are included on the GeneChip Rat Genome 230 2.0 Array. Sequences used in the design of the GeneChip Rat Genome 230 2.0 Array were selected from GenBank, dbEST, and RefSeq. The sequence clusters were created from the UniGene database (Build 99, June 2002) and then refined by analysis and comparison with the publicly available draft assembly of the rat genome from the Baylor College of Medicine Human Genome Sequencing Center (June 2002). The GeneChip Rat Genome 230 2.0 Array includes representation of the RefSeq database sequences and probe sets related to sequences and refined EST clusters previously represented on the GeneChip Rat Genome U34 Set. Oligonucleotide probes complementary to each corresponding sequence are synthesized in situ on the arrays. Eleven pairs of oligonucleotide probes are used to measure the level of transcription of each sequence represented on the GeneChip Rat Genome 230 2.0 Array. Annotations derived from Affymetrix CSV file dated 6/23/2004\nFrom GPL1355\nLast Updated: May 31 2005
#> platform.troubled platform.experimentCount platform.type taxon.name
#> <lgcl> <int> <char> <char>
#> 1: FALSE 296 ONECOLOR rat
#> taxon.scientific taxon.ID taxon.NCBI taxon.database.name taxon.database.ID
#> <char> <int> <int> <char> <int>
#> 1: Rattus norvegicus 3 10116 rn6 86
get_platforms_by_ids(c("GPL1355", "GPL96"))
#> platform.ID platform.shortName
#> <int> <char>
#> 1: 1 GPL96
#> 2: 2 GPL1355
#> platform.name
#> <char>
#> 1: Affymetrix GeneChip Human Genome U133 Array Set HG-U133A
#> 2: Affymetrix GeneChip Rat Genome 230 2.0 Array
#> platform.description
#> <char>
#> 1: The U133 set includes 2 arrays with a total of 44928 entries and was indexed 29-Jan-2002. The set includes over 1,000,000 unique oligonucleotide features covering more than 39,000 transcript variants, which in turn represent greater than 33,000 of the best characterized human genes. Sequences were selected from GenBank, dbEST, and RefSeq. Sequence clusters were created from Build 133 of UniGene (April 20, 2001) and refined by analysis and comparison with a number of other publicly available databases including the Washington University EST trace repository and the University of California, Santa Cruz golden-path human genome database (April 2001 release). In addition, ESTs were analyzed for untrimmed low-quality sequence information, correct orientation, false priming, false clustering, alternative splicing and alternative polyadenylation. Keywords = high density oligonucleotide array\nFrom GPL96\nLast Updated: Mar 09 2006
#> 2: The GeneChip Rat Genome 230 2.0 Array is a powerful tool for toxicology, neurobiology, and other applications using rat as a model organism. - Provides comprehensive coverage of the transcribed rat genome on a single array - Comprised of more than 31,000 probe sets, analyzing over 30,000 transcripts and variants from over 28,000 well-substantiated rat genes - The publicly available draft of the rat genome and leading public rat databases were used to refine sequences and provide a higher quality of data output All probe sets represented on the GeneChip Rat Expression Set 230 are included on the GeneChip Rat Genome 230 2.0 Array. Sequences used in the design of the GeneChip Rat Genome 230 2.0 Array were selected from GenBank, dbEST, and RefSeq. The sequence clusters were created from the UniGene database (Build 99, June 2002) and then refined by analysis and comparison with the publicly available draft assembly of the rat genome from the Baylor College of Medicine Human Genome Sequencing Center (June 2002). The GeneChip Rat Genome 230 2.0 Array includes representation of the RefSeq database sequences and probe sets related to sequences and refined EST clusters previously represented on the GeneChip Rat Genome U34 Set. Oligonucleotide probes complementary to each corresponding sequence are synthesized in situ on the arrays. Eleven pairs of oligonucleotide probes are used to measure the level of transcription of each sequence represented on the GeneChip Rat Genome 230 2.0 Array. Annotations derived from Affymetrix CSV file dated 6/23/2004\nFrom GPL1355\nLast Updated: May 31 2005
#> platform.troubled platform.experimentCount platform.type taxon.name
#> <lgcl> <int> <char> <char>
#> 1: FALSE 400 ONECOLOR human
#> 2: FALSE 296 ONECOLOR rat
#> taxon.scientific taxon.ID taxon.NCBI taxon.database.name taxon.database.ID
#> <char> <int> <int> <char> <int>
#> 1: Homo sapiens 1 9606 hg38 87
#> 2: Rattus norvegicus 3 10116 rn6 86