Title:Integrated Analysis of Transcriptomic and Proteomic Data
VOLUME: 14 ISSUE: 2
Author(s):Saad Haider and Ranadip Pal
Affiliation:Electrical and Computer Engineering, Texas Tech University, Box 43102, Lubbock, TX, 79409, USA.
Keywords:Integrated omics, Data fusion approaches, Transcriptome, Proteome, Joint modeling, Combined analysis review
Abstract:Until recently, understanding the regulatory behavior of cells has been pursued through independent analysis of
the transcriptome or the proteome. Based on the central dogma, it was generally assumed that there exist a direct correspondence
between mRNA transcripts and generated protein expressions. However, recent studies have shown that the
correlation between mRNA and Protein expressions can be low due to various factors such as different half lives and post
transcription machinery. Thus, a joint analysis of the transcriptomic and proteomic data can provide useful insights that
may not be deciphered from individual analysis of mRNA or protein expressions. This article reviews the existing major
approaches for joint analysis of transcriptomic and proteomic data. We categorize the different approaches into eight main
categories based on the initial algorithm and final analysis goal. We further present analogies with other domains and discuss
the existing research problems in this area.
