title: An Integrated Approach for RNA-seq Data Normalization.
abstract: BACKGROUND
  DNA copy number alteration is common in many cancers. Studies have shown that insertion or deletion of DNA sequences can directly alter gene expression, and significant correlation exists between DNA copy number and gene expression. Data normalization is a critical step in the analysis of gene expression generated by RNA-seq technology. Successful normalization reduces/removes unwanted nonbiological variations in the data, while keeping meaningful information intact. However, as far as we know, no attempt has been made to adjust for the variation due to DNA copy number changes in RNA-seq data normalization.
  
  
  RESULTS
  In this article, we propose an integrated approach for RNA-seq data normalization. Comparisons show that the proposed normalization can improve power for downstream differentially expressed gene detection and generate more biologically meaningful results in gene profiling. In addition, our findings show that due to the effects of copy number changes, some housekeeping genes are not always suitable internal controls for studying gene expression.
  
  
  CONCLUSIONS
  Using information from DNA copy number, integrated approach is successful in reducing noises due to both biological and nonbiological causes in RNA-seq data, thus increasing the accuracy of gene profiling.
authors.affiliation: Department of Pathology, School of Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA.; Biostatistics Program, School of Public Health, LSU Health Sciences Center, New Orleans, LA, USA.
authors.forename: Shengping
authors.initials: S
authors.lastname: Yang
authors.affiliation: Biostatistics Program, School of Public Health, LSU Health Sciences Center, New Orleans, LA, USA.
authors.forename: Donald E
authors.initials: DE
authors.lastname: Mercante
authors.affiliation: Department of Computer Science, Xavier University of Louisiana, New Orleans, LA, USA.
authors.forename: Kun
authors.initials: K
authors.lastname: Zhang
authors.affiliation: Biostatistics Program, School of Public Health, LSU Health Sciences Center, New Orleans, LA, USA.
authors.forename: Zhide
authors.initials: Z
authors.lastname: Fang
keywords: DNA copy number alterations; RNA-seq; normalization