{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Chen Y"],"funding":["Silicon Valley Community Foundation","Silicon Valley Community Foundation (SVCF)","Department of Health | National Health and Medical Research Council (NHMRC)","Department of Health | National Health and Medical Research Council"],"pagination":["96"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC8943201"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["9(1)"],"pubmed_abstract":["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 analyse"],"journal":["Scientific data"],"pubmed_title":["R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue."],"pmcid":["PMC8943201"],"funding_grant_id":["1058892","2021-237445","1102742","1176199","1078730"],"pubmed_authors":["Smyth GK","Visvader JE","Pal B","Chen Y","Lindeman GJ"],"additional_accession":[]},"is_claimable":false,"name":"R code and downstream analysis objects for the scRNA-seq atlas of normal and tumorigenic human breast tissue.","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 analyse","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Mar","modification":"2026-04-08T18:08:21.193Z","creation":"2025-04-05T22:18:03.208Z"},"accession":"S-EPMC8943201","cross_references":{"pubmed":["35322042"],"doi":["10.1038/s41597-022-01236-2"]}}