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Defining cell identity beyond the premise of differential gene expression
Identifying genes that define cell identity is a requisite step for characterising cell types and cell states and predicting cell fate choices. By far, the most widely used approach for this task is based on differential expression (DE) of genes, whereby the shift of mean expression are used as the...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Singapore
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087741/ https://www.ncbi.nlm.nih.gov/pubmed/33931812 http://dx.doi.org/10.1186/s13619-021-00083-7 |
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author | Kim, Hani Jieun Tam, Patrick P. L. Yang, Pengyi |
author_facet | Kim, Hani Jieun Tam, Patrick P. L. Yang, Pengyi |
author_sort | Kim, Hani Jieun |
collection | PubMed |
description | Identifying genes that define cell identity is a requisite step for characterising cell types and cell states and predicting cell fate choices. By far, the most widely used approach for this task is based on differential expression (DE) of genes, whereby the shift of mean expression are used as the primary statistics for identifying gene transcripts that are specific to cell types and states. While DE-based methods are useful for pinpointing genes that discriminate cell types, their reliance on measuring difference in mean expression may not reflect the biological attributes of cell identity genes. Here, we highlight the quest for non-DE methods and provide an overview of these methods and their applications to identify genes that define cell identity and functionality. |
format | Online Article Text |
id | pubmed-8087741 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-80877412021-05-14 Defining cell identity beyond the premise of differential gene expression Kim, Hani Jieun Tam, Patrick P. L. Yang, Pengyi Cell Regen Opinion Identifying genes that define cell identity is a requisite step for characterising cell types and cell states and predicting cell fate choices. By far, the most widely used approach for this task is based on differential expression (DE) of genes, whereby the shift of mean expression are used as the primary statistics for identifying gene transcripts that are specific to cell types and states. While DE-based methods are useful for pinpointing genes that discriminate cell types, their reliance on measuring difference in mean expression may not reflect the biological attributes of cell identity genes. Here, we highlight the quest for non-DE methods and provide an overview of these methods and their applications to identify genes that define cell identity and functionality. Springer Singapore 2021-05-01 /pmc/articles/PMC8087741/ /pubmed/33931812 http://dx.doi.org/10.1186/s13619-021-00083-7 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Opinion Kim, Hani Jieun Tam, Patrick P. L. Yang, Pengyi Defining cell identity beyond the premise of differential gene expression |
title | Defining cell identity beyond the premise of differential gene expression |
title_full | Defining cell identity beyond the premise of differential gene expression |
title_fullStr | Defining cell identity beyond the premise of differential gene expression |
title_full_unstemmed | Defining cell identity beyond the premise of differential gene expression |
title_short | Defining cell identity beyond the premise of differential gene expression |
title_sort | defining cell identity beyond the premise of differential gene expression |
topic | Opinion |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8087741/ https://www.ncbi.nlm.nih.gov/pubmed/33931812 http://dx.doi.org/10.1186/s13619-021-00083-7 |
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