<HashMap><database>NODE</database><scores/><additional><omics_type>Transcriptomics</omics_type><submitter>Guangdun Peng</submitter><technology_type>RNA-Seq</technology_type><full_dataset_link>https://www.biosino.org/node/experiment/detail/OEX00021087</full_dataset_link><experiment_platform>Illumina NovaSeq 6000</experiment_platform><experiment_library_layout>Paired</experiment_library_layout><experiment_library_selection>cDNA</experiment_library_selection><experiment_mate_pair>Y</experiment_mate_pair><sample_count>32041</sample_count><tissue>['embryo']</tissue><taxonomy>['Mus']</taxonomy><experiment_protocol>Geo-seq was performed according to the methodology published in (Peng et al., 2019) with modification to adapt to higher throughput. The gene expression pattern (region and level of expression by transcript reads) of the gene of interest was mapped on the corn plot embryonic template, where each kernel represents the cell population sampled at a defined position in the germ layers, to generate a digital rendition of whole mount in situ hybridization.</experiment_protocol><repository>NODE</repository></additional><is_claimable>false</is_claimable><name>geo-seq_plus_spatial_embryogenesis</name><description>By using Geo-seq plus, the mouse embryos from 30 consecutive stages were analyzed comprehensively, generating a spatial transcriptomic view of tissue and organ formation during embryo development.</description><dates><publication>2022-12-01</publication><submission>2022-11-14</submission></dates><accession>OEX00021087</accession><cross_references><NODE>OEP00003746</NODE></cross_references></HashMap>