Chapter 7: High-Performance Computing for Measurement of Cancer Gene Signatures

For precision medicine (PM), the diagnosis and treatment of diseases get assistance from personalized genetic information such as risk alleles and gene expression profiles. Gene signatures are rapidly developing tools for the diagnosis and treatment of cancers. For the measurement of gene signatures, the computation of gene expression levels from RNA-Seq technology is an extremely time-consuming process since the massive amount of RNA-Seq data. Therefore, the acceleration of bioinformatics algorithms had been studied with high-performance computing frameworks, i.e. Apache Hadoop and Spark to process massive data sets in parallel. We illustrate the pipelines for RNA-Seq data processing for gene signatures and collect different HPC methods.