create_rse {recount3} | R Documentation |
Once you have identified a project you want to work with, you can use this
function to construct a recount3
RangedSummarizedExperiment-class
(RSE) object at the gene or exon expression feature level. This function will
retrieve the data, cache it, then assemble the RSE object.
create_rse( project_info, type = c("gene", "exon", "jxn"), annotation = annotation_options(project_info$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_info |
A |
type |
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.
## Find all available human projects human_projects <- available_projects() ## Find the project you are interested in proj_info <- subset( human_projects, project == "SRP009615" & project_type == "data_sources" ) ## Create a RSE object at the gene level rse_gene_SRP009615 <- create_rse(proj_info) ## Explore the resulting RSE gene object rse_gene_SRP009615 ## Information about how this RSE object was made metadata(rse_gene_SRP009615) ## Number of genes by number of samples dim(rse_gene_SRP009615) ## Information about the genes rowRanges(rse_gene_SRP009615) ## Sample metadata colnames(colData(rse_gene_SRP009615)) ## Check how much memory this RSE object uses pryr::object_size(rse_gene_SRP009615) ## Create an RSE object using gencode_v29 instead of gencode_v26 rse_gene_SRP009615_gencode_v29 <- create_rse( proj_info, annotation = "gencode_v29", verbose = FALSE ) rowRanges(rse_gene_SRP009615_gencode_v29) ## Create an RSE object using FANTOM6_CAT instead of gencode_v26 rse_gene_SRP009615_fantom6_cat <- create_rse( proj_info, annotation = "fantom6_cat" ) rowRanges(rse_gene_SRP009615_fantom6_cat) ## Create an RSE object using RefSeq instead of gencode_v26 rse_gene_SRP009615_refseq <- create_rse( proj_info, annotation = "refseq" ) rowRanges(rse_gene_SRP009615_refseq) ## Create an RSE object using ERCC instead of gencode_v26 rse_gene_SRP009615_ercc <- create_rse( proj_info, annotation = "ercc" ) rowRanges(rse_gene_SRP009615_ercc) ## Create an RSE object using SIRV instead of gencode_v26 rse_gene_SRP009615_sirv <- create_rse( proj_info, annotation = "sirv" ) rowRanges(rse_gene_SRP009615_sirv) ## Obtain a list of RSE objects for all gene annotations rses_gene <- lapply(annotation_options(), function(x) { create_rse(proj_info, type = "gene", annotation = x) }) names(rses_gene) <- annotation_options() rses_gene ## Create a RSE object at the exon level rse_exon_SRP009615 <- create_rse( proj_info, type = "exon" ) ## Explore the resulting RSE exon object rse_exon_SRP009615 dim(rse_exon_SRP009615) rowRanges(rse_exon_SRP009615) pryr::object_size(rse_exon_SRP009615) ## Create a RSE object at the exon-exon junction level rse_jxn_SRP009615 <- create_rse( proj_info, type = "jxn" ) ## Explore the resulting RSE exon-exon junctions object rse_jxn_SRP009615 dim(rse_jxn_SRP009615) rowRanges(rse_jxn_SRP009615) pryr::object_size(rse_jxn_SRP009615) ## Obtain a list of RSE objects for all exon annotations ## Not run: rses_exon <- lapply(annotation_options(), function(x) { create_rse(proj_info, type = "exon", annotation = x, verbose = FALSE) }) names(rses_exon) <- annotation_options() ## End(Not run)