Blood (PBMC) Hao Tracks
Peripheral blood mononuclear cells (PBMC) from Hao et al 2020 tracks   (All Single Cell RNA-seq tracks)

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Blood PBMC Cells  Blood (PBMCs) binned by cell type (level 1) from Hao et al 2020  
Blood PBMC Cells 2  Blood PBMCs binned by cell type (level 2) from Hao et al 2020  
Blood PBMC Cells 3  Blood PBMCs binned by cell type (level 3) from Hao et al 2020  
Blood PBMC Donor  Blood PBMCs binned by blood donor from Hao et al 2020  
Blood PBMC Phase  Blood PBMCs binned by phase of cell cycle from Hao et al 2020  
Blood PBMC Time  Blood PBMCs binned by time into experiment from Hao et al 2020  
Assembly: Human Dec. 2013 (GRCh38/hg38)


This track displays data from Integrated analysis of multimodal single-cell data. Human peripheral blood mononuclear cells (PBMCs) taken from pre-vaccinated and post-vaccinated individuals were profiled using both CITE-seq and ECCITE-seq. A total of 57 cell type clusters were identified and each cluster included cells from all 24 samples with rare exceptions. This dataset contains three annotations for cell clustering: Level 1 (8 cell types), Level 2 (30 cell types), Level 3 (57 cell types).

This track collection contains six bar chart tracks of RNA expression in PBMCs where cells are grouped by cell type level 1 (Blood PBMC Cells), cell type level 2 (Blood PBMC Cells 2), cell type level 3 (Blood PBMC Cells 3), donor (Blood PBMC Donor), phase of cell cycle (Blood PBMC Phase), or time into experiment (Blood PBMC Time). The default track displayed is Blood PBMC Cells.

Display Conventions

The cell types are colored by which class they belong to according to the following table.

Color Cell classification

Cells that fall into multiple classes will be colored by blending the colors associated with those classes.


PBMC samples were taken from 8 volunteers ages 20-49 enrolled in an HIV vaccine trial (NCT01578889). A total of 24 blood samples were collected at 3 time points: day 0 (the day before), day 3, and day 7 after the administration of a VSV-vectored HIV vaccine. Samples were collected at these different time points to minimize batch effects. Cells were then divided into separate aliquots for modified versions of the 3' CITE-seq and 5' ECCITE-seq staining protocols. In the 3' CITE-seq staining protocol, the samples are simultaneously stained with the antibody and unique hashtag. Whereas, 5' ECCITE-seq samples are stained first with a unique hashtag. 3' libraries were loaded into 8 lanes of a 10x Genomics Chip B using the 10x Genomics 3' v3 kit. 5' libraries were loaded into 2 lanes of a 10x Genomics Chip A using the 10x Genomics V(D)J kit (v1). Both 3' and 5' libraries were pooled together and sequenced on an Illumina Novaseq S4 flowcell. In total, 210,911 cells were profiled after quality control and doublet filtration.

The cell/gene matrix and cell-level metadata was downloaded from the UCSC Cell Browser. The UCSC command line utility matrixClusterColumns, matrixToBarChart, and bedToBigBed were used to transform these into a bar chart format bigBed file that can be visualized. The coloring was done by defining colors for the broad level cell classes and then using another UCSC utility, hcaColorCells, to interpolate the colors across all cell types. The UCSC utilities can be found on our download server.

Data Access

The raw bar chart data can be explored interactively with the Table Browser or the Data Integrator. For automated analysis, the data may be queried from our REST API. Please refer to our mailing list archives for questions, or our Data Access FAQ for more information.


Thanks to Yuhan Hao, Stephanie Hao, and to the many authors who worked on producing and publishing this data set. The data were integrated into the UCSC Genome Browser by Jim Kent and Brittney Wick then reviewed by Jairo Navarro. The UCSC work was paid for by the Chan Zuckerberg Initiative.


Hao Y, Hao S, Andersen-Nissen E, Mauck WM 3rd, Zheng S, Butler A, Lee MJ, Wilk AJ, Darby C, Zager M et al. Integrated analysis of multimodal single-cell data. Cell. 2021 Jun 24;184(13):3573-3587.e29. PMID: 34062119; PMC: PMC8238499