2023 Fiscal Year Annual Research Report
Inferring cells differentiation processes from single-cell Multiome ATACseq+RNAseq data.
| Project/Area Number |
22K21301
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| Research Institution | The University of Tokyo |
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Principal Investigator |
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| Project Period (FY) |
2022-08-31 – 2024-03-31
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| Keywords | multiomics / Expression estimation / ATAC-seq / RNA-seq / Macrophages polarization |
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| Outline of Annual Research Achievements |
We designed and trained a fuzzy logic model of gene expression for a dataset involving Macrophages polarized/de-polarized at different stages (M0,M1,M2) and time points (0,6,12,24 hrs.) to test our designed model.
We were able to reproduce important gene expression signatures of cells at different time points and stages.
We then used our model to estimate the expression levels of a set of selected genes. These genes were selected to have a "hysteresis" effect during polarization. We observed interesting patterns in the estimated gene expression that will possibly be integrated into a manuscript we are currently preparing.
Thanks to the integration of expression and open-chromatin data, we were able to track down the hysteresis effect to the enhancers of the selected genes.
In summary, we were able to use our fuzzy model in a real scenario with interesting results.
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| Remarks |
The repository is still private until we public the manuscript we are preparing.
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