A comprehensive genomic and transcriptomic dataset of triple-negative breast cancers

被引:0
作者
Qingwang Chen
Yaqing Liu
Yuechen Gao
Ruolan Zhang
Wanwan Hou
Zehui Cao
Yi-Zhou Jiang
Yuanting Zheng
Leming Shi
Ding Ma
Jingcheng Yang
Zhi-Ming Shao
Ying Yu
机构
[1] Fudan University,State Key Laboratory of Genetic Engineering, School of Life Sciences and Human Phenome Institute
[2] Fudan University Shanghai Cancer Center,Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Precision Cancer Medicine Center
[3] Fudan University,Shanghai Cancer Hospital/Cancer Institute
[4] Fudan University,Fudan
[5] Greater Bay Area Institute of Precision Medicine,Gospel Joint Research Center for Precision Medicine
来源
Scientific Data | / 9卷
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摘要
Molecular subtyping of triple-negative breast cancer (TNBC) is essential for understanding the mechanisms and discovering actionable targets of this highly heterogeneous type of breast cancer. We previously performed a large single-center and multiomics study consisting of genomics, transcriptomics, and clinical information from 465 patients with primary TNBC. To facilitate reusing this unique dataset, we provided a detailed description of the dataset with special attention to data quality in this study. The multiomics data were generally of high quality, but a few sequencing data had quality issues and should be noted in subsequent data reuse. Furthermore, we reconduct data analyses with updated pipelines and the updated version of the human reference genome from hg19 to hg38. The updated profiles were in good concordance with those previously published in terms of gene quantification, variant calling, and copy number alteration. Additionally, we developed a user-friendly web-based database for convenient access and interactive exploration of the dataset. Our work will facilitate reusing the dataset, maximize the values of data and further accelerate cancer research.
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