Systems Genetic Approach

Posted on Mar 16, 2017 0 Comments

There are my notes when I read the paper called System Genetic Approach.

Summary

• the causal modeling algorithms NEO
• co-expression network algorithm, wMICA

Introduction

• GWAS only modest success

  • complex, heterogeneous nature of the disease

• minimize these complexities in genetic studies of model organisms such as mice

  • classical QTL linkage analyses in mice have identified a number of novel HF-related genes

• previous work association analyses identified both known and novel genes contributing to hypertrophy

• an extension of this study though the modeling of biological networks

  • an improved version of the Maximal Information Component Analysis(MICA) algorithms

  • several modules that showed significant association to HF-related phenotypes were identified

  • NEO algorithm to develop a directed network with predicted casual interactions among the module genes.

  • using an in vitro model we validated several of these casual links

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Results

Gene Network Analysis Using Weighted MICA

• HDMP: Hybrid Mouse Diversity Panel
• prior research using HMDP to generate mRNA co-expression networks.

• MICA: an unbiased gene network construction algorithm

  • several conceptual improvement over traditional co-expression methods.
  • captures both linear and nonlinear interactions within the data
  • allow genes to be spread proportionally across multiple modules
• horvath: weighted network construction algorithms, in which all edges are included in the analysis, have greater versatility and power than unweighted algorithms, in which edges are included or exclude based on a hard threshold.
• improve upon origin algorithm and develop a modified, weighted, form of MICA, called wMICA.
  • the application of wMICA to the analysis of HF, using gene expression data across inbred strains of mice from the HMDP HF study.
• Filter probes for transcripts that were significantly expressed in at least 25% of samples and had a coefficient of variation of at least 5%. Final a set of 8126 probes, representing 31.6% of the total probes on the array.
• Three gene networks, 20 modules each.
  • one based only on transcripts from the untreated hearts,
  • one based only on the treated
  • a third based on the change in gene expression between these two conditions two measures.
• Two measures were used for the preliminary analyses of these networks.
  • calculate significant GO enrichments within each of these modules at several module membership cutoffs.
  • use principal component analysis(PCA) to identify the first principal component of each module.

New words

versatility

inbred

cardiac

hypertrophy

mimic

chronic

adrenergic

ventricular

chamber

heterogeneous

putative

myocytes

impair

therapeutic