create_rse_manual {recount3} | R Documentation |
This function is used internally by create_rse()
to construct a recount3
RangedSummarizedExperiment-class
object that contains the base-pair coverage counts at the gene
or exon
feature level for a given annotation.
create_rse_manual( project, project_home = project_homes(organism = organism, recount3_url = recount3_url), type = c("gene", "exon", "jxn"), organism = c("human", "mouse"), annotation = annotation_options(organism), bfc = recount3_cache(), jxn_format = c("ALL", "UNIQUE"), recount3_url = getOption("recount3_url", "http://duffel.rail.bio/recount3"), verbose = getOption("recount3_verbose", TRUE) )
project |
A |
project_home |
A |
type |
A |
organism |
A |
annotation |
A |
bfc |
A BiocFileCache-class
object where the files will be cached to, typically created by
|
jxn_format |
A |
recount3_url |
A |
verbose |
A |
A RangedSummarizedExperiment-class object.
https://doi.org/10.12688/f1000research.12223.1 for details on the base-pair coverage counts used in recount2 and recount3.
Other internal functions for accessing the recount3 data:
annotation_ext()
,
file_retrieve()
,
locate_url_ann()
,
locate_url()
,
project_homes()
,
read_counts()
,
read_metadata()
## Unlike create_rse(), here we create an RSE object by ## fully specifying all the arguments for locating this study rse_gene_SRP009615_manual <- create_rse_manual( "SRP009615", "data_sources/sra" ) rse_gene_SRP009615_manual ## Check how much memory this RSE object uses pryr::object_size(rse_gene_SRP009615_manual) ## Test with a collection that has a single sample ## NOTE: this requires loading the full data for this study when ## creating the RSE object rse_gene_ERP110066_collection_manual <- create_rse_manual( "ERP110066", "collections/geuvadis_smartseq", recount3_url = "http://snaptron.cs.jhu.edu/data/temp/recount3" ) rse_gene_ERP110066_collection_manual ## Check how much memory this RSE object uses pryr::object_size(rse_gene_ERP110066_collection_manual) ## Mouse example rse_gene_DRP002367_manual <- create_rse_manual( "DRP002367", "data_sources/sra", organism = "mouse" ) rse_gene_DRP002367_manual ## Information about how this RSE was made metadata(rse_gene_DRP002367_manual) ## Test with a collection that has one sample, at the exon level ## NOTE: this requires loading the full data for this study (nearly 6GB!) ## Not run: rse_exon_ERP110066_collection_manual <- create_rse_manual( "ERP110066", "collections/geuvadis_smartseq", type = "exon", recount3_url = "http://snaptron.cs.jhu.edu/data/temp/recount3" ) rse_exon_ERP110066_collection_manual ## Check how much memory this RSE object uses pryr::object_size(rse_exon_ERP110066_collection_manual) # 409 MB ## Test with a collection that has one sample, at the junction level ## NOTE: this requires loading the full data for this study system.time(rse_jxn_ERP110066_collection_manual <- create_rse_manual( "ERP110066", "collections/geuvadis_smartseq", type = "jxn", recount3_url = "http://snaptron.cs.jhu.edu/data/temp/recount3" )) rse_jxn_ERP110066_collection_manual ## Check how much memory this RSE object uses ## NOTE: this doesn't run since 2 files are missing on the test site! pryr::object_size(rse_jxn_ERP110066_collection_manual) ## End(Not run) ## Not run: ## For testing and debugging project <- "ERP110066" project_home <- "collections/geuvadis_smartseq" project <- "SRP009615" project_home <- "data_sources/sra" type <- "gene" organism <- "human" annotation <- "gencode_v26" jxn_format <- "ALL" bfc <- recount3_cache() recount3_url <- "http://idies.jhu.edu/recount3/data" verbose <- TRUE ## End(Not run)