<HashMap><database>biostudies-arrayexpress</database><scores/><additional><submitter>Nadezhda Azbukina</submitter><organism>Homo sapiens</organism><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/E-MTAB-15622</full_dataset_link><description>In order to systematically investigate, to which extent cell lines and experimental batches affect the consistency of organoid patterning, we conducted a multiplexed morphogen patterning experiment to study the reproducibility of the effects induced by retinoic acid, FGF-8, SHH and CHIR. We have tested influence of 2 neural induction methods, 2 experimental batches and 4 cell lines: H1 (XY), H9 (XX), WTC (XY) and WIBJ (XX) on cell type composition consistency after morphogen patterning using single-cell transcriptomic readout (Parse Bioscience) and pooling 3 organoids for each condition.</description><repository>biostudies-arrayexpress</repository><sample_protocol>Sample Collection - After d21 in culture 3 organoids per condition per cell line were dissociated individually using CyBio FeliX liquid handler robot with thermoshaker. For dissociation we used a papain-based dissociation kit (Miltenyi Neural dissociation kit). Each organoid was dissociated using 410uL of enzyme mix 1 and 6uL of enzyme mix 2. Then single cell suspension from the same condition were pooled together (H1 and H9; WTC and WIBJ2).</sample_protocol><sample_protocol>Sequencing - Libraries were sequenced in S2 flowcell with Illumina Nova Seq technology, using paired-end 64/8/8/58 configuration.</sample_protocol><sample_protocol>Nucleic Acid Extraction - Each individual single cell suspension has been followed by  fixation and  permeabilization procedures, which were performed according to the manufacturer specification (ParseBiosciences, cell fixation kit v3, CF100).</sample_protocol><sample_protocol>Library Construction - Collected samples were processed for highly multiplexed single-cell RNA sequencing (scRNA-seq) using a split-pool combinatorial barcoding kit (ParseBiosciences, WT Mega kit v3, MG100).</sample_protocol><figure_sub>Organization</figure_sub><figure_sub>MINSEQE Score</figure_sub><figure_sub>Assays and Data</figure_sub><figure_sub>Processed Data</figure_sub><figure_sub>MAGE-TAB Files</figure_sub><data_protocol>Data Transformation - Transcript counts were normalized to the total number of counts for that cell, multiplied by a scaling factor of 10,000 and subsequently natural-log transformed. We used scanpy python package (v1.10.3).</data_protocol><data_protocol>Sequence Alignment - We used Parse Biosciences Software (v1.3.1) to demultiplex barcodes, map to hg38 human transcriptome and generate count matrix.</data_protocol><omics_type>Metabolomics</omics_type><omics_type>Unknown</omics_type><omics_type>Transcriptomics</omics_type><omics_type>Genomics</omics_type><omics_type>Proteomics</omics_type><instrument_platform>Illumina NovaSeq X</instrument_platform><study_type>RNA-seq of coding RNA from single cells</study_type><species>Homo sapiens</species><pubmed_authors>Nadezhda Azbukina</pubmed_authors><pubmed_authors>Fátima Sanchís Calleja</pubmed_authors></additional><is_claimable>false</is_claimable><name>scRNA-seq of human neural brain organoids patterning reproducibility screening</name><description>In order to systematically investigate, to which extent cell lines and experimental batches affect the consistency of organoid patterning, we conducted a multiplexed morphogen patterning experiment to study the reproducibility of the effects induced by retinoic acid, FGF-8, SHH and CHIR. We have tested influence of 2 neural induction methods, 2 experimental batches and 4 cell lines: H1 (XY), H9 (XX), WTC (XY) and WIBJ (XX) on cell type composition consistency after morphogen patterning using single-cell transcriptomic readout (Parse Bioscience) and pooling 3 organoids for each condition.</description><dates><release>2025-10-01T00:00:00Z</release><modification>2026-05-27T12:16:28.418Z</modification><creation>2025-09-23T12:01:48.657Z</creation></dates><accession>E-MTAB-15622</accession><cross_references><ENA>ERP180513</ENA><EFO>EFO_0002944</EFO><EFO>EFO_0004170</EFO><EFO>EFO_0005684</EFO><EFO>EFO_0004917</EFO><EFO>EFO_0005518</EFO><EFO>EFO_0003816</EFO><EFO>EFO_0004184</EFO></cross_references></HashMap>