Tree-Based Co-Clustering Identifies Chromatin Accessibility Patterns Associated With Hematopoietic Lineage Structure
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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2021-10-01
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| Series: | Frontiers in Genetics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2021.707117/full |
| _version_ | 1819104397308723200 |
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| author | Thomas B. George Nathaniel K. Strawn Sivan Leviyang |
| author_facet | Thomas B. George Nathaniel K. Strawn Sivan Leviyang |
| author_sort | Thomas B. George |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-22T02:05:42Z |
| format | Article |
| id | doaj.art-868aa20def57415ca76a7eef616a9d7c |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-22T02:05:42Z |
| publishDate | 2021-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-868aa20def57415ca76a7eef616a9d7c2022-12-21T18:42:32ZengFrontiers Media S.A.Frontiers in Genetics1664-80212021-10-011210.3389/fgene.2021.707117707117Tree-Based Co-Clustering Identifies Chromatin Accessibility Patterns Associated With Hematopoietic Lineage StructureThomas B. GeorgeNathaniel K. StrawnSivan LeviyangChromatin 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.https://www.frontiersin.org/articles/10.3389/fgene.2021.707117/fullchromatin accessibilityhematopoiesisclusteringtree (graphs)ATACseqepigenetics |
| spellingShingle | Thomas B. George Nathaniel K. Strawn Sivan Leviyang Tree-Based Co-Clustering Identifies Chromatin Accessibility Patterns Associated With Hematopoietic Lineage Structure Frontiers in Genetics chromatin accessibility hematopoiesis clustering tree (graphs) ATACseq epigenetics |
| title | Tree-Based Co-Clustering Identifies Chromatin Accessibility Patterns Associated With Hematopoietic Lineage Structure |
| title_full | Tree-Based Co-Clustering Identifies Chromatin Accessibility Patterns Associated With Hematopoietic Lineage Structure |
| title_fullStr | Tree-Based Co-Clustering Identifies Chromatin Accessibility Patterns Associated With Hematopoietic Lineage Structure |
| title_full_unstemmed | Tree-Based Co-Clustering Identifies Chromatin Accessibility Patterns Associated With Hematopoietic Lineage Structure |
| title_short | Tree-Based Co-Clustering Identifies Chromatin Accessibility Patterns Associated With Hematopoietic Lineage Structure |
| title_sort | tree based co clustering identifies chromatin accessibility patterns associated with hematopoietic lineage structure |
| topic | chromatin accessibility hematopoiesis clustering tree (graphs) ATACseq epigenetics |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2021.707117/full |
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