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Intro
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Single-cell data have identified some immune cell types that are expanded or depleted in autoimmunity
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Modeling dynamic regulatory elements to find disease-critical cell states
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Identifying cell-state-dependent peaks within each cell type using a continuous Poisson GLM framework
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Example peak accessibility profiles reflect the nature of dynamic versus invariant peaks
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Annotating the genome based on peak sets of interest
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We can identify peak-gene-cell state trios associated with autoimmune diseases
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Once we have identified a cell state of interest, how can we systematically learn its active gene regulatory programs?
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Stochasticity: transcriptional bursting
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Transcriptional heterogeneity is propagated from a TF to its target genes in sequential steps, each of which creates a time delay...
Description:
Explore stochasticity in transcription through this 50-minute Medical and Population Genetics Primer lecture from the Broad Institute. Delve into single-cell data analysis of immune cell types in autoimmunity, modeling dynamic regulatory elements, and identifying cell-state-dependent peaks using continuous Poisson GLM frameworks. Examine peak accessibility profiles, genome annotation based on peak sets, and the identification of peak-gene-cell state trios associated with autoimmune diseases. Investigate transcriptional bursting and how transcriptional heterogeneity propagates from transcription factors to target genes. Gain insights into cutting-edge genetics research and its applications in understanding complex traits and diseases.

Stochasticity in Transcription - MPG Primer 2023

Broad Institute
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