A Method for Difference Analysis of Genomic Data Mining in Breast Cancer

The emergence of high-throughput sequencing technology provides access to large volumes of biological data. Mining important information from such a huge amount of genomic data is a big challenge and requires complicated data analysis techniques. In the present study, difference analysis technology was applied to mine breast cancer genomic data for important information about aggressiveness. Meanwhile, GO enrichment analysis and KEGG enrichment analysis were used to further extract significant information closely associated with breast cancer aggressiveness. In addition, visualization of the analysis results was provided. Finally, significant differential genes in breast cancer genomics data were obtained by differential analysis techniques and possible future perspectives are presented.