Exploratory and Model-Based Analysis of ScHi-C Data

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United States Simons Institute for the Theory of Computing
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Published on ● Video Link: https://www.youtube.com/watch?v=fHFMdyvQ-eg


Duration: 34:36
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Sunduz Keles (University of Wisconsin, Madison)
https://simons.berkeley.edu/talks/exploratory-and-model-based-analysis-schi-c-data
Computational Challenges in Very Large-Scale 'Omics'

Single-cell high-throughput chromatin conformation capture methodologies (scHi-C) enable profiling long-range genomic interactions; however, data from these technologies are prone to technical noise and biases that hinder downstream analysis. I will discuss normalization and denoising issues of scHi-C data by introducing a simple normalization approach named BandNorm and a deep generative modeling framework, scVI-3D, to account for scHi-C specific biases. I will also introduce single-cell gene associating domain (scGAD) scores as a dimension reduction and exploratory analysis tool for scHi-C data and illustrate how this approach enables integration of scHi-C data with other single cell data modalities.



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Tags:
Simons Institute
theoretical computer science
UC Berkeley
Computer Science
Theory of Computation
Theory of Computing
Computational Challenges in Very Large-Scale 'Omics'
Sunduz Keles