THUNDER: A reference-free deconvolution method to infer cell type proportions from bulk Hi-C data Article Swipe
Bryce Rowland
,
Ruth Huh
,
Zoey Hou
,
Cheynna Crowley
,
Jia Wen
,
Yin Shen
,
Ming Hu
,
Paola Giusti‐Rodríguez
,
Patrick F. Sullivan
,
Yun Li
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pgen.1010102
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1371/journal.pgen.1010102
Hi-C data provide population averaged estimates of three-dimensional chromatin contacts across cell types and states in bulk samples. Effective analysis of Hi-C data entails controlling for the potential confounding factor of differential cell type proportions across heterogeneous bulk samples. We propose a novel unsupervised deconvolution method for inferring cell type composition from bulk Hi-C data, the Two-step Hi-c UNsupervised DEconvolution appRoach (THUNDER). We conducted extensive simulations to test THUNDER based on combining two published single-cell Hi-C (scHi-C) datasets. THUNDER more accurately estimates the underlying cell type proportions compared to reference-free methods (e.g., TOAST, and NMF) and is more robust than reference-dependent methods (e.g. MuSiC). We further demonstrate the practical utility of THUNDER to estimate cell type proportions and identify cell-type-specific interactions in Hi-C data from adult human cortex tissue samples. THUNDER will be a useful tool in adjusting for varying cell type composition in population samples, facilitating valid and more powerful downstream analysis such as differential chromatin organization studies. Additionally, THUNDER estimated contact profiles provide a useful exploratory framework to investigate cell-type-specificity of the chromatin interactome while experimental data is still rare.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1371/journal.pgen.1010102
- https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1010102&type=printable
- OA Status
- gold
- Cited By
- 13
- References
- 54
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4220789938
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4220789938Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1371/journal.pgen.1010102Digital Object Identifier
- Title
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THUNDER: A reference-free deconvolution method to infer cell type proportions from bulk Hi-C dataWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
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2022-03-08Full publication date if available
- Authors
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Bryce Rowland, Ruth Huh, Zoey Hou, Cheynna Crowley, Jia Wen, Yin Shen, Ming Hu, Paola Giusti‐Rodríguez, Patrick F. Sullivan, Yun LiList of authors in order
- Landing page
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https://doi.org/10.1371/journal.pgen.1010102Publisher landing page
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https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1010102&type=printableDirect link to full text PDF
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://journals.plos.org/plosgenetics/article/file?id=10.1371/journal.pgen.1010102&type=printableDirect OA link when available
- Concepts
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Thunder, Deconvolution, Population, Cell type, Biology, Cell, Computer science, Algorithm, Physics, Genetics, Meteorology, Demography, SociologyTop concepts (fields/topics) attached by OpenAlex
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13Total citation count in OpenAlex
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2025: 1, 2024: 4, 2023: 5, 2022: 3Per-year citation counts (last 5 years)
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54Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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