HCA Data Explorer

Profiling of CD34+ cells from human bone marrow to understand hematopoiesis

Differentiation is among the most fundamental processes in cell biology. Single cell RNA-seq studies have demonstrated that differentiation is a continuous process and in particular cell states are observed to reside on largely continuous spaces. We have developed Palantir, a graph based algorithm to model continuities in cell state transitions and cell fate choices. Modeling differentiation as a Markov chain, Palantir determines probabilities of reaching terminal states from cells in each intermediate state. The entropy of these probabilities represent the differentiation potential of the cell in the corresponding state. Applied to single cell RNA-seq dataset of CD34+ hematopoietic cells from human bone marrows, Palantir accurately identified key events leading up to cell fate commitment. Integration with ATAC-seq data from bulk sorted populations helped identify key regulators that correlate with cell fate specification and commitment.

Manu SettySloan Kettering Institutemanu.talanki@gmail.com
Dana Pe'erSloan Kettering Institutepeerster@gmail.com
Manu Setty1
Vaidotas Kiseliovas1
Dana Pe'er (Principal Investigator)1
1Sloan Kettering Institute
Parisa Nejad

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Analysis Portals


Project Label



Homo sapiens

Sample Type


Anatomical Entity

bone marrow

Organ Part


Selected Cell Types

CD34-positive, CD38-negative hematopoietic stem cell

Model Organ

bone marrow

Disease Status (Specimen)


Disease Status (Donor)


Development Stage

human adult stage

Library Construction Method

10x 3' v2

Nucleic Acid Source

single cell

Paired End


File Format

5 file formats

Cell Count Estimate


Donor Count

bam9 file(s)csv1 file(s)fastq.gz24 file(s)h5ad3 file(s)loom10 file(s)