18.191.189.101=18.1
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&id=35322042&retmode=xml&tool=pubfacts&email=info@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b490818.191.189.101=18.1
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&term=human+breast&datetype=edat&usehistory=y&retmax=5&tool=pubfacts&email=info@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b490818.191.189.101=18.1
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&WebEnv=MCID_67957a4afefb948e3c0c92c9&query_key=1&retmode=xml&retmax=5&tool=pubfacts&email=info@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908 R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue. | LitMetric

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.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8943201PMC
http://dx.doi.org/10.1038/s41597-022-01236-2DOI Listing

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