Profiling of CD34+ cells from human bone marrow to understand hematopoiesis
Updated October 20, 2021Differentiation 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.
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Analysis Portals
NoneProject Label
HumanHematopoieticProfilingSpecies
Sample Type
Anatomical Entity
Organ Part
Selected Cell Types
Model Organ
Disease Status (Specimen)
Disease Status (Donor)
Development Stage
Library Construction Method
Nucleic Acid Source
Paired End
falseAnalysis Protocol
optimus_post_processing_v1.0.0, optimus_v4.2.2File Format
Cell Count Estimate
1.5MDonor Count
3