-- DBMS: bigquery
CREATE TABLE `isb-cgc-bq.HTAN_versioned.scRNAseq_CHOP_seurat_pool_logNorm_gini_FiveHD_10Xv3_downsample10000HSPC_r2`
(
  iObs INT64 OPTIONS(description="Index to cell barcodes."),
  iVar INT64 OPTIONS(description="Index to gene IDs."),
  X_value FLOAT64 OPTIONS(description="Expression value for a given gene and cell."),
  Cell_Name STRING OPTIONS(description="Cell Barcode"),
  nCount_RNA FLOAT64 OPTIONS(description="Number of counts per cell."),
  nFeature_RNA INT64 OPTIONS(description="Number of genes identified per cell."),
  Sample STRING OPTIONS(description="Sample ID"),
  Perc_mito FLOAT64 OPTIONS(description="Percent mitochondrial RNA considering total counts."),
  Seurat_Clusters INT64 OPTIONS(description="seurat cluster, resolution = 1.6"),
  Pseudotime FLOAT64 OPTIONS(description="Pseudotime value by Slingshot"),
  S_Score FLOAT64 OPTIONS(description="S phase score, computed by seurat "),
  G2M_Score FLOAT64 OPTIONS(description="G2M phase score, computed by seurat "),
  Phase STRING OPTIONS(description="Estimated phase of the cell cycle. G2M,S,G1"),
  HeatShock_Score FLOAT64 OPTIONS(description="Heat Shock score, computed by seurat "),
  Cell_Type STRING OPTIONS(description="Final cell type annotation"),
  Gene_Name STRING OPTIONS(description="Gene Symbol")
)
OPTIONS(
  friendly_name="HTAN HG38 SCRNASEQ GENE EXPRESSION NORMAL HEMATOPOIETIC REFERENCE R2 VERSIONED",
  description="Data was derived in April 2022 from an H5AD file (Synapse ID: syn25147383) submitted by the CHOP HTAN Center. This data set contains log normalized gene expression counts from normal hematopoietic healthy cells from 5 pediatric donors. Data was generated using the 10X Genomics V3 chemistry and was processed using CellRanger, where reads were mapped to HG38. The 15 filtered (5 donors each with 3 sorted samples) gene-by-cell count matrices were combined into a bigger gene-by-cell count matrix. To prevent sorted progenitor cells from dominating the cell composition, we down-sampled the sorted cells to 12,000, about half of the live cells. The combined matrix was converted to a Seurat object, with the fraction of mitochondrial UMI and sample information added as the metadata. We next applied the same procedure as for integrating patient scRNA-Seq data, except using top 1,500 VEGs, the first 20 PCs, and only regressing out confounding factors of the total UMI count per cell and the fraction of mitochondrial UMIs per cell.",
  labels=[("access", "open"), ("reference_genome", "hg38"), ("data_type", "gene_expression"), ("program", "htan"), ("source", "htan-chop"), ("category", "processed_-omics_data"), ("status", "current")]
);

INSERT INTO `isb-cgc-bq.HTAN_versioned.scRNAseq_CHOP_seurat_pool_logNorm_gini_FiveHD_10Xv3_downsample10000HSPC_r2` (iObs, iVar, X_value, Cell_Name, nCount_RNA, nFeature_RNA, Sample, Perc_mito, Seurat_Clusters, Pseudotime, S_Score, G2M_Score, Phase, HeatShock_Score, Cell_Type, Gene_Name) VALUES (2403, 12167, 1.464545, 'donor2111_live_GTCTAGAGTCGTTCAA', 3007.0, 1095, 'donor2111_live', 0.1476063829787234, 1, 9.335115004965967, -0.1024314032429578, -0.0439582428844182, 'G1', -0.1307860914573386, 'Mono', 'AC004687.1'), (2403, 12526, 1.464545, 'donor2111_live_GTCTAGAGTCGTTCAA', 3007.0, 1095, 'donor2111_live', 0.1476063829787234, 1, 9.335115004965967, -0.1024314032429578, -0.0439582428844182, 'G1', -0.1307860914573386, 'Mono', 'IMPACT'), (2403, 3866, 1.464545, 'donor2111_live_GTCTAGAGTCGTTCAA', 3007.0, 1095, 'donor2111_live', 0.1476063829787234, 1, 9.335115004965967, -0.1024314032429578, -0.0439582428844182, 'G1', -0.1307860914573386, 'Mono', 'PTGER4'), (2403, 10971, 1.464545, 'donor2111_live_GTCTAGAGTCGTTCAA', 3007.0, 1095, 'donor2111_live', 0.1476063829787234, 1, 9.335115004965967, -0.1024314032429578, -0.0439582428844182, 'G1', -0.1307860914573386, 'Mono', 'MGRN1'), (2403, 10272, 1.464545, 'donor2111_live_GTCTAGAGTCGTTCAA', 3007.0, 1095, 'donor2111_live', 0.1476063829787234, 1, 9.335115004965967, -0.1024314032429578, -0.0439582428844182, 'G1', -0.1307860914573386, 'Mono', 'SLC25A29');