{"database":"biostudies-arrayexpress","file_versions":[],"scores":null,"additional":{"submitter":["Aziz Belkadi"],"organism":["Homo sapiens"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/E-MTAB-16219"],"description":["We performed 10x Genomics single-cell RNA sequencing (scRNA-seq) on 12 urine samples from kidney transplant recipients. These urine samples contain a mixture of donor-derived kidney cells and recipient-derived immune and bladder cells. To our knowledge, this is the first study to apply single-cell transcriptomics to urine samples from kidney allograft recipients."],"repository":["biostudies-arrayexpress"],"sample_protocol":["Nucleic Acid Extraction - The cell pellet was resuspended in 2% BSA-DPBS and subjected to Ficoll-Paque density gradient centrifugation at 1312 g for 20 minutes at room temperature. Cells were then collected and washed with 2% BSA-DPBS, followed by centrifugation at 400 g for 10 minutes at room temperature. The pellet was resuspended in 0.5% BSA-DPBS, filtered through a 30 µm cell strainer, and centrifuged again at 200 g for 6 minutes at room temperature. Finally, the cells were resuspended in 0.5% BSA-DPBS.","Sequencing - The library was sequenced on Illumina HiSeq 2500 platform as follows: 26 bp (Read1) and 98 bp (Read2). The sequencing was performed to obtain 150–200 million reads (each for Read1 and Read2).","Library Construction - We used the 10x Genomics' Chromium Single Cell 3' Reagent Kit v3 (first three samples) or v3.1 (subsequent nine samples), according to the manufacturer's instructions, for the library preparation.","Sample Collection - Freshly voided urine was passed through a 40 µm cell strainer and centrifuged at 400 g for 10 minutes at room temperature."],"figure_sub":["Organization","MINSEQE Score","Assays and Data","Processed Data","MAGE-TAB Files"],"data_protocol":["Data Transformation - Raw single-cell gene expression counts were generated using the Cell Ranger (10x Genomics) pipeline. For each sample, cellranger count was used to produce a filtered gene-by-cell UMI count matrix containing only high-quality barcodes identified as cells. When multiple libraries were combined, sequencing depth normalization was performed using cellranger aggr with the default mapped read depth normalization mode to ensure comparable read counts across samples. The resulting matrices contain untransformed UMI counts, which were subsequently normalized during downstream analysis (log-normalization)."],"omics_type":["Metabolomics","Unknown","Transcriptomics","Genomics","Proteomics"],"instrument_platform":["Illumina HiSeq 2500"],"study_type":["RNA-seq of coding RNA from single cells"],"species":["Homo sapiens"],"pubmed_authors":["Thanganami Muthukumar","Aziz Belkadi"],"additional_accession":[]},"is_claimable":false,"name":"Single cell RNA-seq on kidney allograft urine samples","description":"We performed 10x Genomics single-cell RNA sequencing (scRNA-seq) on 12 urine samples from kidney transplant recipients. These urine samples contain a mixture of donor-derived kidney cells and recipient-derived immune and bladder cells. To our knowledge, this is the first study to apply single-cell transcriptomics to urine samples from kidney allograft recipients.","dates":{"release":"2026-07-09T00:00:00Z","modification":"2026-07-09T13:53:42.986Z","creation":"2025-11-22T20:16:18.047Z"},"accession":"E-MTAB-16219","cross_references":{"ENA":["ERP185505"],"EFO":["EFO_0002944","EFO_0004170","EFO_0005684","EFO_0005518","EFO_0003816","EFO_0004184"]}}