Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.10.22.350611v1?rss=1 Authors: Baccini, F., Bianchini, M., Geraci, F. Abstract: In this paper, we show that quantifying histone modifications by counting the number of high-resolution peaks in each gene allows to build profiles of these epigenetic marks, associating them to a phenotype. The significance of this approach is verified by applying graph-cut techniques for assessing the differentiation between myeloid and lymphoid cells in haematopoiesis, i.e. the process through which all the different types of blood cells originate starting from a unique cell type. The experiments are conducted on a population of samples from 24 cell types involved in haematopoiesis. Six profiles are constructed for each cell type, based on a different histone modification signal. Following the experimentally verified idea that the peak number distribution per gene behaves similarly to gene expression, the profile computation employs standard differential analysis tools to find genes whose epigenetic modifications are related to a given phenotype. Next, six similarity networks of cell types are constructed, based on each histone modification, and then combined into a unique one through similarity network fusion. Finally, the similarity networks are transformed into dissimilarity graphs, to which two different cuts are applied and compared to evaluate the classic differentiation between myeloid and lymphoid cells. The results show that all histone modifications contribute almost equally to the myeloid/lymphoid differentiation, and this is also confirmed by the analysis of the fused network. However, they also suggest that histone modifications may not be the only mechanism for regulating the differentiation of hematopoietic cells. Copy rights belong to original authors. Visit the link for more info