DOI: 10.5061/dryad.8pk0p2ns8
title: scRNA data from: Organization of the human Intestine at single cell resolution

description: The human adult intestinal system is a complex organ that is approximately
 9 meters long and performs a variety of complex functions including
 digestion, nutrient absorption, and immune surveillance. We performed
 snRNA-seq on 8 regions of of the human intestine (duodenum,
 proximal-jejunum, mid-jejunum, ileum, ascending colon, transverse colon,
 descending colon, and sigmoid colon) from 9 donors (B001, B004, B005,
 B006, B008, B009, B010, B011, and B012). In the corresponding paper, we
 find cell compositions differ dramatically across regions of the intestine
 and demonstrate the complexity of epithelial subtypes. We map gene
 regulatory differences in these cells suggestive of a regulatory
 differentiation cascade, and associate intestinal disease heritability
 with specific cell types. These results describe the complexity of the
 cell composition, regulation, and organization in the human intestine, and
 serve as an important reference map for understanding human biology and
 disease.
description: For a detailed description of each of the steps to obtain this
 data see the detailed materials and methods in the associated manuscript.
 Briefly, intestine pieces from 8 different sites across the small
 intestine and colon were flash frozen. Nuclei were isolated from each
 sample and the resulting nuclei were processed with either 10x scRNA-seq
 using Chromium Next GEM Single Cell 3’ Reagent Kits v3.1 (10x Genomics,
 1000121) or Chromium Next GEM Chip G Single Cell Kits (10x Genomics,
 1000120) or 10x multiome sequencing using Chromium Next GEM Single Cell
 Multiome ATAC + Gene Expression Kits (10x Genomics, 1000283).
 Initial processing of snRNA-seq data was done with the Cell
 Ranger Pipeline (https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/what-is-cell-ranger) by first running cellranger mkfastq to demultiplex the bcl files and then running cellranger count. Since nuclear RNA was sequenced, data were aligned to a pre-mRNA reference. Initial processing of the mutiome data, including alignment and generation of fragments files and expression matrices, was performed with the Cell Ranger ARC Pipeline. The raw expression matrices from these pipelines are included here. Downstream processing was performed in R, using the Seurat package.
description: The dataset includes the raw expression matrices generated by
 Cell Ranger or Cell Ranger ARC for each individual sample in the study.
 Each raw expression matrix is saved as 3 files (***_barcodes.tsv.gz,
 ***_features.tsv.gz, and ***_matrix.mtx.gz) where *** is replaced by the
 sample name. These files can be opened in any programming
 language.  In addition to the individual expression
 matrices, the processed scRNA data is included as Seurat objects saved as
 .rds files. The Seurat objects are divided into an object for all immune
 cells (clustered_immune_object.rds), an object for all stromal cells
 (clustered_stromal_object.rds), and four objects for epithelial cells from
 the four primary regions of the intestine (clustered_duodenum_object.rds,
 clustered_jejunum_object.rds, clustered_ileum_object.rds, and
 clustered_colon_object.rds). Subclustered populations of enteroendocrine
 (clustered_enteroendocrine_object.rds) and specialized secretory
 epithelial cells (clustered_secretory_special_object.rds) are also
 included as separate Seurat objects. The Seurat objects contain the
 DecontX corrected counts (corrected for ambient RNA contamination) in
 addition to the raw counts. These files can be opened in R.
 There are also the files that include umap x and y coordinates
 and our cell type annotations for the filtered cells in the study named
 ***_UMAP_CellType.tsv. These files have four columns, Cell ID (unique name
 of the cell consisting of sample and RNA barcode), UMAP_1 (umap coordinate
 1), UMAP_2 (umap coordinate 2), and the CellType (cell type annotation
 that we assigned to each cell). These tsv files can be opened in any
 programming language.  A metadata file is included that
 contains the names of all samples in the study (SampleNameRNA), whether
 the sample was processed with the multiome kit (Multiome), the donor
 (Donor), and the location in the intestine the sample was collected from
 (Location).