## ----style, echo=FALSE-------------------------------------------------------- knitr::opts_chunk$set(error=FALSE, warning=FALSE, message=FALSE) ## ----------------------------------------------------------------------------- library(scRNAseq) all.ds <- surveyDatasets() all.ds ## ----------------------------------------------------------------------------- # Find all datasets involving pancreas. searchDatasets("pancreas")[,c("name", "title")] # Find all mm10 datasets involving pancreas or neurons. searchDatasets( defineTextQuery("GRCm38", field="genome") & (defineTextQuery("neuro%", partial=TRUE) | defineTextQuery("pancrea%", partial=TRUE)) )[,c("name", "title")] ## ----------------------------------------------------------------------------- sce <- fetchDataset("zeisel-brain-2015", "2023-12-14") sce ## ----------------------------------------------------------------------------- sce <- fetchDataset("baron-pancreas-2016", "2023-12-14", path="human") sce ## ----------------------------------------------------------------------------- assay(sce) sce <- fetchDataset("baron-pancreas-2016", "2023-12-14", path="human", realize.assays=TRUE) class(assay(sce)) ## ----------------------------------------------------------------------------- str(fetchMetadata("zeisel-brain-2015", "2023-12-14")) ## ----------------------------------------------------------------------------- library(SingleCellExperiment) sce <- SingleCellExperiment(list(counts=matrix(rpois(1000, lambda=1), 100, 10))) rownames(sce) <- sprintf("GENE_%i", seq_len(nrow(sce))) colnames(sce) <- head(LETTERS, 10) ## ----------------------------------------------------------------------------- meta <- list( title="My dataset", description="This is my dataset", taxonomy_id="10090", genome="GRCh38", sources=list( list(provider="GEO", id="GSE12345"), list(provider="PubMed", id="1234567") ), maintainer_name="Chihaya Kisaragi", maintainer_email="kisaragi.chihaya@765pro.com" ) ## ----------------------------------------------------------------------------- # Simple case: you only have one dataset to upload. staging <- tempfile() saveDataset(sce, staging, meta) list.files(staging, recursive=TRUE) # Complex case: you have multiple datasets to upload. staging <- tempfile() dir.create(staging) saveDataset(sce, file.path(staging, "foo"), meta) saveDataset(sce, file.path(staging, "bar"), meta) # etc. ## ----------------------------------------------------------------------------- alabaster.base::readObject(file.path(staging, "foo")) ## ----eval=FALSE--------------------------------------------------------------- # gypsum::uploadDirectory(staging, "scRNAseq", "my_dataset_name", "my_version") ## ----eval=FALSE--------------------------------------------------------------- # fetchDataset("my_dataset_name", "my_version") ## ----eval=FALSE--------------------------------------------------------------- # gypsum::rejectProbation("scRNAseq", "my_dataset_name", "my_version") ## ----------------------------------------------------------------------------- sessionInfo()