4.6 Article

Tree-Based Co-Clustering Identifies Chromatin Accessibility Patterns Associated With Hematopoietic Lineage Structure

Journal

FRONTIERS IN GENETICS
Volume 12, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2021.707117

Keywords

chromatin accessibility; hematopoiesis; clustering; tree (graphs); ATACseq; epigenetics

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The study explores the association between chromatin accessibility and hematopoietic cell types using a novel co-clustering approach, showing that 80% of cell type associated accessibility variation can be captured through specific cell type clusters and genomic locus clusters. The cell type clusters reflect coherent components of the differentiation tree in hematopoiesis. Traditional clustering methods lead to more dispersed cell type clusters compared to the tree-based algorithm presented in the study.
Chromatin accessibility, as measured by ATACseq, varies between hematopoietic cell types in different lineages of the hematopoietic differentiation tree, e.g. T cells vs. B cells, but methods that associate variation in chromatin accessibility to the lineage structure of the differentiation tree are lacking. Using an ATACseq dataset recently published by the ImmGen consortium, we construct associations between chromatin accessibility and hematopoietic cell types using a novel co-clustering approach that accounts for the structure of the hematopoietic, differentiation tree. Under a model in which all loci and cell types within a co-cluster have a shared accessibility state, we show that roughly 80% of cell type associated accessibility variation can be captured through 12 cell type clusters and 20 genomic locus clusters, with the cell type clusters reflecting coherent components of the differentiation tree. Using publicly available ChIPseq datasets, we show that our clustering reflects transcription factor binding patterns with implications for regulation across cell types. We show that traditional methods such as hierarchical and kmeans clusterings lead to cell type clusters that are more dispersed on the tree than our tree-based algorithm. We provide a python package, chromcocluster, that implements the algorithms presented.

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