- Really cool paper from Haas/Trumpp/Velten labs
- Precise definitions of hematopoietic cells in the bone marrow based on surface marker expression and 462 mRNAs
- Useful for people who want to isolate cell types with FACS but also lots of good marker genes for using with scRNA-seq
- Found that the surface protein is only modestly affected by ageing but the majority of AML cells clustered away from the healthy differentiation trajectory > "Our data resource and bioinformatic advances enable the efficient identification and isolation of any molecularly defined cell state from blood and bone marrow while laying the grounds for reconciling flow cytometry and single-cell genomics data across human tissues."
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- Nice summary of the case for using ontologies to define cell types
- Highlights
- "Before the age of single-cell genomics, a rigorous definition was usually not necessary. Colloquially, a cell type is a category of cells in the body that performs a certain function."
- "such a fuzzy definition does not suffice as a foundational definition from which one could go on to create 'reference maps'"
- "as researchers measure more cells, they tend to find more 'cell types'"
- "First, let’s get the obvious out of the way: the concept of “cell type” is human-made. Nature does not create categories, rather, we create categories in our minds."
- "I argue that one can define a cell type to simply be a subset of cell states in the cellular state space. For example, when one talks about a “T cell”, they are inherently talking about all states in the cell state space in which the cell is performing a function that we have named “T cell”."
- "The idea of defining cell types to be subsets of cell states enables one to define disease cell types... Because diseased cell types are represented in the same framework as any other cell type, we can add them to an ontology of cell types"
- "multiple batches [...] results in two disconnected, and approximately isomorphic subgraphs."
- "a useful mental model for thinking about cell types, cell states, and for placing open problems in bioinformatics into a common conceptual framework"
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