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R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue
Breast cancer is a common and highly heterogeneous disease. Understanding cellular diversity in the mammary gland and its surrounding micro-environment across different states can provide insight into cancer development in the human breast. Recently, we published a large-scale single-cell RNA expres...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8943201/ https://www.ncbi.nlm.nih.gov/pubmed/35322042 http://dx.doi.org/10.1038/s41597-022-01236-2 |
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author | Chen, Yunshun Pal, Bhupinder Lindeman, Geoffrey J. Visvader, Jane E. Smyth, Gordon K. |
author_facet | Chen, Yunshun Pal, Bhupinder Lindeman, Geoffrey J. Visvader, Jane E. Smyth, Gordon K. |
author_sort | Chen, Yunshun |
collection | PubMed |
description | Breast cancer is a common and highly heterogeneous disease. Understanding cellular diversity in the mammary gland and its surrounding micro-environment across different states can provide insight into cancer development in the human breast. Recently, we published a large-scale single-cell RNA expression atlas of the human breast spanning normal, preneoplastic and tumorigenic states. Single-cell expression profiles of nearly 430,000 cells were obtained from 69 distinct surgical tissue specimens from 55 patients. This article extends the study by providing quality filtering thresholds, downstream processed R data objects, complete cell annotation and R code to reproduce all the analyses. Data quality assessment measures are presented and details are provided for all the bioinformatic analyses that produced results described in the study. |
format | Online Article Text |
id | pubmed-8943201 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89432012022-04-08 R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue Chen, Yunshun Pal, Bhupinder Lindeman, Geoffrey J. Visvader, Jane E. Smyth, Gordon K. Sci Data Data Descriptor Breast cancer is a common and highly heterogeneous disease. Understanding cellular diversity in the mammary gland and its surrounding micro-environment across different states can provide insight into cancer development in the human breast. Recently, we published a large-scale single-cell RNA expression atlas of the human breast spanning normal, preneoplastic and tumorigenic states. Single-cell expression profiles of nearly 430,000 cells were obtained from 69 distinct surgical tissue specimens from 55 patients. This article extends the study by providing quality filtering thresholds, downstream processed R data objects, complete cell annotation and R code to reproduce all the analyses. Data quality assessment measures are presented and details are provided for all the bioinformatic analyses that produced results described in the study. Nature Publishing Group UK 2022-03-23 /pmc/articles/PMC8943201/ /pubmed/35322042 http://dx.doi.org/10.1038/s41597-022-01236-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Data Descriptor Chen, Yunshun Pal, Bhupinder Lindeman, Geoffrey J. Visvader, Jane E. Smyth, Gordon K. R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue |
title | R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue |
title_full | R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue |
title_fullStr | R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue |
title_full_unstemmed | R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue |
title_short | R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue |
title_sort | r code and downstream analysis objects for the scrna-seq atlas of normal and tumorigenic human breast tissue |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8943201/ https://www.ncbi.nlm.nih.gov/pubmed/35322042 http://dx.doi.org/10.1038/s41597-022-01236-2 |
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