Mosaddek Hossain Sk Md, Ray Sumanta, Mukhopadhyay Anirban
Department of Computer Science and Engineering, Aliah University, Kolkata, West Bengal, 700156, India.
Department of Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, 741235, India.
BMC Bioinformatics. 2017 Mar 20;18(1):181. doi: 10.1186/s12859-017-1590-3.
Analysis of gene expression data provides valuable insights into disease mechanism. Investigating relationship among co-expression modules of different stages is a meaningful tool to understand the way in which a disease progresses. Identifying topological preservation of modular structure also contributes to that understanding.
HIV-1 disease provides a well-documented progression pattern through three stages of infection: acute, chronic and non-progressor. In this article, we have developed a novel framework to describe the relationship among the consensus (or shared) co-expression modules for each pair of HIV-1 infection stages. The consensus modules are identified to assess the preservation of network properties. We have investigated the preservation patterns of co-expression networks during HIV-1 disease progression through an eigengene-based approach.
We discovered that the expression patterns of consensus modules have a strong preservation during the transitions of three infection stages. In particular, it is noticed that between acute and non-progressor stages the preservation is slightly more than the other pair of stages. Moreover, we have constructed eigengene networks for the identified consensus modules and observed the preservation structure among them. Some consensus modules are marked as preserved in two pairs of stages and are analyzed further to form a higher order meta-network consisting of a group of preserved modules. Additionally, we observed that module membership (MM) values of genes within a module are consistent with the preservation characteristics. The MM values of genes within a pair of preserved modules show strong correlation patterns across two infection stages.
We have performed an extensive analysis to discover preservation pattern of co-expression network constructed from microarray gene expression data of three different HIV-1 progression stages. The preservation pattern is investigated through identification of consensus modules in each pair of infection stages. It is observed that the preservation of the expression pattern of consensus modules remains more prominent during the transition of infection from acute stage to non-progressor stage. Additionally, we observed that the module membership values of genes are coherent with preserved modules across the HIV-1 progression stages.
基因表达数据分析为疾病机制提供了有价值的见解。研究不同阶段共表达模块之间的关系是理解疾病进展方式的一个有意义的工具。识别模块结构的拓扑保留也有助于这种理解。
HIV-1疾病呈现出一个记录完备的从感染的三个阶段发展的模式：急性期、慢性期和非进展期。在本文中，我们开发了一个新颖的框架来描述HIV-1感染各阶段每一对之间的共识（或共享）共表达模块之间的关系。识别共识模块以评估网络属性的保留情况。我们通过基于特征基因的方法研究了HIV-1疾病进展过程中共表达网络的保留模式。
我们发现共识模块的表达模式在三个感染阶段的转变过程中具有很强的保留性。特别是，注意到在急性期和非进展期之间的保留性略高于其他阶段对。此外，我们为识别出的共识模块构建了特征基因网络，并观察了它们之间的保留结构。一些共识模块在两对阶段中被标记为保留，并进一步分析以形成一个由一组保留模块组成的高阶元网络。此外，我们观察到一个模块内基因的模块隶属度（MM）值与保留特征一致。一对保留模块内基因的MM值在两个感染阶段显示出很强的相关模式。
我们进行了广泛的分析，以发现从三个不同HIV-1进展阶段的微阵列基因表达数据构建的共表达网络的保留模式。通过识别每对感染阶段中的共识模块来研究保留模式。观察到在从急性期到非进展期的感染转变过程中，共识模块表达模式的保留更为突出。此外，我们观察到基因的模块隶属度值在HIV-1进展阶段与保留模块是一致的。
