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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
BCMA: An integrative and versatile database for multi-scale and multi-omics molecular atlas of breast cancer
Wenbo Guo1, Zikang Yin1, Qinglin Mei1
1MOE Key Lab of Bioinformatics, BNRIST Bioinformatics Division, Department of Automation, Tsinghua University, Beijing, China.
Abstract:
Breast cancer (BC) is one of the most common cancer types among women worldwide. Understanding the complex molecular and cellular characteristics of BC is crucial for advancing precision treatment. To enable more reliable and reproducible biological discoveries, it is critical to collect molecular data from diverse BC cohorts and establish an integrative, versatile analysis platform. Here, we present BCMA (Breast Cancer Molecular Atlas, http://lifeome.net/database/bcma/), a multi-scale, multi-omics BC database that encompasses 6 bulk multi-omics datasets and 9 single-cell transcriptomics datasets, collectively covering 5424 cases and 236,363 cells. The BCMA systemically characterizes the molecular features of BC, including gene mutations, copy number alterations, RNA expression, miRNA expression, DNA methylation, as well as clinical phenotypes and cell heterogeneity. Meanwhile, a user-friendly interface for gene-centered search is provided, achieving the clinical information statistics, genomic events analysis, differential multi-omics feature identification, functional enrichment analysis, survival analysis, co-expression analysis, as well as single-cell gene expression profiling and cell type annotation. This platform holds great potential to enhance the understanding of molecular characteristics underlying BC and to facilitate the identification of disease-associated biomarkers.
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