{"database":"GEO","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Other":["ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE294nnn/GSE294759/"]},"type":"primary"},"statusCode":"OK","statusCodeValue":200}],"scores":null,"additional":{"omics_type":["Other"],"species":[" Mus musculus","Homo sapiens"],"gds_type":["Other"],"full_dataset_link":["https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE294759"],"repository":["GEO"],"entry_type":["GSE"],"additional_accession":[]},"is_claimable":false,"name":"Application of spatial transcriptomics across organoids for a high-resolution spatial whole-transcriptome benchmarking dataset","description":"Stem cell-derived organoids hold promise to model tissue-specific disease. To enable this, it is crucial to assess how transcriptional signatures, cellular organisation and composition of organoids compare to in vivo counterparts. However, spatial transcriptomics has been challenging to apply to organoids to elucidate regional molecular identity. This study presents the first systematic profiling of multiple stem cell derived organoid models (brain, heart muscle, heart valve, kidney, lung, cartilage, and haematopoietic) with Stereo-seq, a full transcriptome, spatial assay using on-chip in situ RNA capture. It describes assay optimisation for characterisation, use of multiple organoid samples on a single chip, assesses limitations in RNA capture efficiency compared to reference tissues. Furthermore, it introduces a bespoke analysis method that partitions samples into regions for characterisation. These findings inform future works to characterise organoids using spatial transcriptomics, providing insights in optimising RNA capture of multiple organoids across a chip and regional analysis.","dates":{"publication":"2026/04/08"},"accession":"GSE294759","cross_references":{"GSM":["GSM8919111","GSM8919110","GSM8919109","GSM8919117","GSM8919116","GSM8919115","GSM8919114","GSM8919113","GSM8919112"],"GPL":["28330","29480"],"GSE":["294759"],"taxon":[" Mus musculus","Homo sapiens"]}}