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.
To reference this project, please use the following link:
Supplementary links are provided by contributors and represent items such as additional data which can’t be hosted here; code that was used to analyze this data; or tools and visualizations associated with this specific dataset.
For information regarding data sharing and data use, please see our Data Access Policy.
Selected Cell Types
Disease Status (Specimen)
Disease Status (Donor)
Library Construction Method
Nucleic Acid Source
Cell Count Estimate1.5M