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ANC Workshop: Andreas Kapourani and Joseph Cronin, Chair: Cole Hurwitz

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What
  • ANC Workshop Talk
When Oct 30, 2018
from 11:00 AM to 12:00 PM
Where IF 4.31/4.33
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Andreas Kapourani

Melissa: Bayesian clustering and imputing of single cell methylomes

Measurements of DNA methylation at the single cell level are promising to revolutionise our understanding of epigenetic control of gene expression. Yet, intrinsic limitations of the technology result in very sparse coverage of CpG sites (around 5% to 20% coverage), effectively limiting the analysis repertoire to a semi-quantitative level. Here we introduce Melissa (MEthyLation Inference for Single cell Analysis), a Bayesian hierarchical method to quantify spatially-varying methylation profiles across genomic regions from single-cell bisulfite sequencing data (scBS-seq). Melissa clusters individual cells based on local methylation patterns, enabling the discovery of epigenetic differences and similarities among individual cells. The clustering also acts as an effective regularisation method for imputation of methylation on unassayed CpG sites, enabling transfer of information between individual cells. We show both on simulated and real data sets that Melissa provides accurate and biologically meaningful clusterings, and state-of-the-art imputation performance.

 

Joseph Cronin

Altered responses in primary visual cortex in a mouse model of autism spectrum disorders 

Autism spectrum disorders (ASD) are a broad range of neurodevelopmental disorders that commonly coincide with intellectual disability (ID). ASD/ID can arise from a diverse set of genetic and environmental factors, with the vast majority of genetic links involving genes that regulate neural activity and plasticity. SynGap+/- mice are established animal models of SynGap haploinsufficiency, a common monogenic disorder. The cellular and behavioural effects of this disorder have been well studied, however relatively little is known about how these impairments manifest themselves at the network level . This talk will discuss work on using a support vector machine (SVM) to decode stimulus information from inferred spiking activity in the visual cortex of wild type (WT) and SynGap+/- mice. Results suggest differences in overall performance and temporal resolution of decoding between the two genotypes.