Advances and challenges in epigenomic single-cell sequencing applications
Understanding multicellular physiology and pathobiology requires analysis of the relationship between genotype, chromatin organisation and phenotype. In the multi-omics era, many methods exist to investigate biological processes across the genome, transcriptome, epigenome, proteome and metabolome. U...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
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Elsevier
2020
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| _version_ | 1797100479860178944 |
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| author | Philpott, M Cribbs, AP Brown Jr, T Brown Sr, T Oppermann, U |
| author_facet | Philpott, M Cribbs, AP Brown Jr, T Brown Sr, T Oppermann, U |
| author_sort | Philpott, M |
| collection | OXFORD |
| description | Understanding multicellular physiology and pathobiology requires analysis of the relationship between genotype, chromatin organisation and phenotype. In the multi-omics era, many methods exist to investigate biological processes across the genome, transcriptome, epigenome, proteome and metabolome. Until recently, this was only possible for populations of cells or complex tissues, creating an averaging effect that may obscure direct correlations between multiple layers of data. Single-cell sequencing methods have removed this averaging effect, but computational integration after profiling distinct modalities separately may still not completely reflect underlying biology. Multiplexed assays resolving multiple modalities in the same cell are required to overcome these shortcomings and have the potential to deliver unprecedented understanding of biology and disease. |
| first_indexed | 2024-03-07T05:38:07Z |
| format | Journal article |
| id | oxford-uuid:e4a0f8a5-44cb-4006-ad99-a96fa78fe9a4 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T05:38:07Z |
| publishDate | 2020 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:e4a0f8a5-44cb-4006-ad99-a96fa78fe9a42022-03-27T10:18:02ZAdvances and challenges in epigenomic single-cell sequencing applicationsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:e4a0f8a5-44cb-4006-ad99-a96fa78fe9a4EnglishSymplectic ElementsElsevier2020Philpott, MCribbs, APBrown Jr, TBrown Sr, TOppermann, UUnderstanding multicellular physiology and pathobiology requires analysis of the relationship between genotype, chromatin organisation and phenotype. In the multi-omics era, many methods exist to investigate biological processes across the genome, transcriptome, epigenome, proteome and metabolome. Until recently, this was only possible for populations of cells or complex tissues, creating an averaging effect that may obscure direct correlations between multiple layers of data. Single-cell sequencing methods have removed this averaging effect, but computational integration after profiling distinct modalities separately may still not completely reflect underlying biology. Multiplexed assays resolving multiple modalities in the same cell are required to overcome these shortcomings and have the potential to deliver unprecedented understanding of biology and disease. |
| spellingShingle | Philpott, M Cribbs, AP Brown Jr, T Brown Sr, T Oppermann, U Advances and challenges in epigenomic single-cell sequencing applications |
| title | Advances and challenges in epigenomic single-cell sequencing applications |
| title_full | Advances and challenges in epigenomic single-cell sequencing applications |
| title_fullStr | Advances and challenges in epigenomic single-cell sequencing applications |
| title_full_unstemmed | Advances and challenges in epigenomic single-cell sequencing applications |
| title_short | Advances and challenges in epigenomic single-cell sequencing applications |
| title_sort | advances and challenges in epigenomic single cell sequencing applications |
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