Mining Cancer Transcriptomes: Bioinformatic Tools and the Remaining Challenges

Mol Diagn Ther. 2017 Jun;21(3):249-258. doi: 10.1007/s40291-017-0264-1.

Abstract

The development of next-generation sequencing technologies has had a profound impact on the field of cancer genomics. With the enormous quantities of data being generated from tumor samples, researchers have had to rapidly adapt tools or develop new ones to analyse the raw data to maximize its value. While much of this effort has been focused on improving specific algorithms to get faster and more precise results, the accessibility of the final data for the research community remains a significant problem. Large amounts of data exist but are not easily available to researchers who lack the resources and experience to download and reanalyze them. In this article, we focus on RNA-seq analysis in the context of cancer genomics and discuss the bioinformatic tools available to explore these data. We also highlight the importance of developing new and more intuitive tools to provide easier access to public data and discuss the related issues of data sharing and patient privacy.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology / methods*
  • Computational Biology / standards
  • Confidentiality / ethics
  • Gene Expression Profiling / methods*
  • Genomics / methods
  • High-Throughput Nucleotide Sequencing / methods
  • Humans
  • Information Dissemination / methods
  • Neoplasms / genetics*
  • Sequence Analysis, RNA / methods
  • Transcriptome