{"id": "package:92bb7cd2-f9f8-4979-9332-c825fdf58972", "name": "PR1643-142-samples-raw-gene-counts_thumbnail.jpg", "self_uri": "https://services.scicrunch.io/sparc/drs/v1/objects/92bb7cd2-f9f8-4979-9332-c825fdf58972", "size": 1240089, "created_time": "2022-02-28T01:46:30,627393Z", "updated_time": "2022-02-28T01:46:31,327772Z", "version": "2", "mime_type": "image/jpeg", "checksums": [{"checksum": "8e46866a7abd938f8d45f852adc179eefaff175d3a437ad965c0ebddfac1635d", "type": "sha256"}], "access_methods": [{"type": "s3", "access_url": {"url": "s3://prd-sparc-discover50-use1/116/files/derivative/PR1643-142-samples-raw-gene-counts_thumbnail.jpg"}, "region": "us-east-1"}], "dataset": {"id": "116", "doi": "DOI:10.26275/az1n-uv7s", "title": "Spatially tracked single-cell-scale RNAseq of porcine right atrial ganglionic plexus (RAGP) neurons", "description": "Neuronal samples from the porcine RAGP were collected through laser capture microdissection and run through single-cell-scale RNAseq\n", "abstract": "**Study purpose:** The purpose of this study was to create comprehensive atlas of the cardiac ICN in porcine RAGP at a cellular level providing gene expression profiles of cardiac neurons on single cell resolution. We developed an approach to appreciate the 3D organization of the intracardiac neurons, ICN, while at the same time permitting single cell transcriptomics and connectomics.\n\n**Data collection:** This dataset contains results of single-cell-scale RNAseq run on 142 spatially tracked regional neuronal samples collected through Laser Capture Microdissection (LCM). After QC, 90 samples remain with detectable expression of over 15,000 genes, yielding 1,350,000 datapoints. These single-cell-scale samples were processed through RNAseq using a novel 3seq protocol, specifically designed for LCM samples (Foley et al. 2019). Fastq and bam files are included for all 142 samples that were assayed as well as raw counts and normalized counts for the 90 samples that passed QC.\n\n**Primary Conclusion**: A novel protocol was used to perform single-cell-scale RNAseq on LCM samples, allowing, for the first time, spatially tracked single-cell-scale RNAseq. Imaging of these samples as they were collected through LCM allowed spatial tracking of these samples within their 3D context, allowing the transcriptional profiles of these neurons to be mapped back to their anatomical locations."}}