Synthetic Lethality In Networks

Question

[Tonig]

Hi all,

I have a network built using the list of genes coming from a microarray experiemnt, i used Genemania in order to map interactions from co-expression databases, and now I want to know which genes could involved in synthetic lethality.

My approach was the next:

I used igraph package to load and analyze the network, I tried to find those genes that are Hubs using Hub authority and Hub scores functions and the removing them and their interactions from the networks to show that they are involved in Synthetic lethality, however the network didn't show a signifficant change ( i.e didn't collapse it) Do you know any other package in Bioconductor or an existing alternative outside R? Suggestions will be appreciated

Thanks in advance

Answer 1

[Khader Shameer]

Synthetic lethality is a well defined concept in biology. I think it may be a bit difficult to detect synthetic lethality exclusively from the gene expression based network data. If you have/genome/transcriptome data this would have been possible.

The approach you mentioned is more of a quantitative network analysis approach than a synthetic lethality analysis. Also, it is not clear to me what is your control in the analysis approach you mentioned.

A set of network analysis tools/packages are discussed here. I have also used NetworkAnalyzer (Cytoscape plugin, available in batch-mode and also as a jar file for command-line execution) for computing multiple network statistics (network diameter, network radius, network desnsity, clustering coefficient, topological coefficients, betweenness centrality, closeness centrality, stress centrality, network heterogeneity, degree distribution etc.) Another tool FANMOD can be used to detect network motifs within your derived network, but again you need a control network to get meaningul insight from such analyses.