Video transcript: Visualising complex networks
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Dr Tom Freeman, Group Leader, The Roslin
My name is Tom Freeman. I'm in the division of genetics and genomics at the Roslin Institute. What I am going to show you today is essentially a programme we have been working on now for the last five years which allows us to essentially visualise data as networks.
Camera shows the 3-D world generated by the software
So what you are seeing here is essentially a large amount of data which is derived from a genomics platform called 'microarrays' and these microarrays allow us to measure the level of activity of every gene in the human body or mouse or whatever the ray is designed for. In this world then what we have done, in this data here is our attempt to begin to understand how genes are used across a whole range of different populations of mouse cells which are derived from the immune system. So these graphs here are essentially a display of a large amount of data. In each case here, each one of these nodes as they are called, or as we say 'spheres', represents a gene and those genes are connected to other genes by something called an edge. The edge in this case relates to how similar that gene is expressed to that gene so that we can begin to see quite complex relationships such as here, where all of these genes essentially in this purple cluster here are genes which have a very similar expression pattern so there are lots of edges between them.
If I wanted to look at some of these genes then I can pull up the second tool within this and this allows me to display a given group of genes.
Camera shows the gene cross-section generated by the software
Lets just click on one at random here. And what you can see is that there is a whole bunch of genes across 300 samples here which are expressed in this one particular cell type and this begins to tell something about what those genes might do and if I click on this side then I can see the type of genes these are and this shows the profile of how they are expressed. Likewise I can move through the graph and begin to see different patterns of expression and these different patterns of expression relate to the functional biology of the genes of interest. What this allows us then to do is have a resource which we can understand something about gene function and their role of these genes in protecting animals from disease by understanding how they are regulated, what cells they are expressed by allows us to begin to unpick some of the complexity which is there in biology and shows us how they are expressed.