Publications

Full Publication List: Pubmed


Selected publications:


Coexpression networks identify brain region–specific enhancer RNAs in the human brain

Yao et al. Nature Neuroscience (2015).

Abstract: Despite major progress in identifying enhancer regions on a genome-wide scale, the majority of available data are limited to model organisms and human transformed cell lines. We have identified a robust set of enhancer RNAs (eRNAs) expressed in the human brain and constructed networks assessing eRNA-gene coexpression interactions across human fetal brain and multiple adult brain regions. Our data identify brain region–specific eRNAs and show that enhancer regions expressing eRNAs are enriched for genetic variants associated with autism spectrum disorders.

Associated website and data are available here.


The landscape of circular RNA expression in the human brain

Gokool et al. Biological Psychiatry (2019).

Abstract: Circular RNAs (circRNAs) are enriched in the mammalian brain and are upregulated in response to neuronal differentiation and depolarisation. These RNA molecules, formed by non-canonical back-splicing, have both regulatory and translational potential. Here, we carried out an extensive characterisation of circRNA expression in the human brain, in nearly two hundred human brain samples, from both healthy individuals and autism cases.We identify hundreds of novel circRNAs and demonstrate that circRNAs are not expressed stochastically, but rather as major isoforms. We characterise inter-individual variability of circRNA expression in the human brain and show that inter-individual variability is less pronounced than variability between cerebral cortex and cerebellum. Finally, we identify a circRNA co-expression module upregulated in autism samples, thereby adding another layer of complexity to the transcriptome changes observed in autism brain.These data provide a comprehensive catalogue of circRNAs as well as a deeper insight into their expression in the human brain, and are available as a free resource in browsable format.

Associated website and data are available here.


TDAview: an online visualization tool for topological data analysis

Walsh et al. Bioinformatics (2020).

Abstract TDAview is an online tool for topological data analysis and visualization. It implements the Mapper algorithm for topological data analysis and provides extensive graph visualization options. TDAview is a user-friendly tool that allows biologists and clinicians without programming knowledge to harness the power of topological data analysis. TDAview supports an analysis and visualization mode in which a Mapper graph is constructed based on user-specified parameters, followed by graph visualization. It can also be used in a visualization only mode in which TDAview is used for visualizing the data properties of a Mapper graph generated using other open-source software. The graph visualization options allow data exploration by graphical display of meta-data variable values for nodes and edges, as well as the generation of publishable figures. TDAview can handle large datasets, with tens of thousands of data points, and thus has a wide rande of applications for high-dimensional data, including the construction of topology-based gene co-expression networks. TDAview is a free online tool available at https://voineagulab.github.io/TDAview/. The source code, usage documentation and example data are available at TDAview GitHub repository: https://github.com/Voineagulab/TDAview.