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DBS-Pro PBMCs

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posted on 2024-03-28, 09:37 authored by Pontus HöjerPontus Höjer, Abel Nagy, Humam SigaHumam Siga, Jun Wang, Håkan Jönsson, Petter BrodinPetter Brodin, Amelie E. Karlström, Afshin Ahmadian

This resource contains data generated using the method DBS-Pro (Droplet Barcode Sequencing for Protein analysis) for single cells for the manuscript "Identification of Major Immune Cell Lineages with DBS-Pro". The data was generated using peripheral blood mononuclear cells (PBMCs) extracted from a single healthy donor from which two libraries were prepared (P29859_1001, P29859_1002). The data quantifies surface proteins on single cells using a panel of six marker antibodies (CD3, CD4, CD8, CD19, CD14, CD45) and one isotype control antibody to quantify background signal. The antibodies are conjugated to oligonucleotides containing an antibody barcode and a UMI sequence. The stained cells are barcoded in droplet emulsions and then sequenced to get out quantitative information about the cells.

The data includes raw FASTQ files (*.fastq.gz). The FASTQs were also run through the DBS-Pro pipeline (https://github.com/FrickTobias/DBS-Pro, v0.4) to generate *data.tsv.gz and *counts.h5ad files.

The TSV files *data.tsv.gz contain the following columns:

  • Barcode: The corrected droplet barcode
  • Target: The antibody target (marker) name. E.g. CD3
  • UMI: The UMI sequence
  • ReadCount: Number of reads with this droplet barcode, target and UMI combination
  • Sample: Sample name

For convenience, [anndata](https://anndata.readthedocs.io/en/latest/index.html) `h5ad` files with count matrices are also generated for each sample. These can be used for downstream analysis using [Scanpy](https://scanpy.readthedocs.io/en/stable/). To import the data use the following code:

```

import scanpy as sc

adata = sc.read_h5ad("mysample.h5ad")

adata

```


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KTH Royal Institute of Technology

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