Blast To Cytoscape
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11.1 years ago
c.v.oflynn ▴ 100

Hi Guys,

I am trying to view the results of an all vs all blastp of some sequences with cytoscape.

I've been using the Blast2SimilarityGraph app to read in my data (blast -m 8 + fasta file) and then a few other apps to do what i want. This works fine.

However my problem is that Blast2SimilarityGraph does not work for larger files (>~19,000 seqs). I am not sure why,It is not a memory issue as i am using quite a powerful box, it seems more likely to be a default limit.

Does any have any suggestions for a better way to read in my files or an alternative app?

Appreciate your time guys

Ciaran

blast cytoscape protein network • 3.9k views
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You will have to define "Does not work." I am not familiar with the particular Cytoscape plugin, but having ~19000 nodes (and potentially 19000*2 edges) sounds like it is _very_ demanding, and the plugin was probably not designed to handle that many connections, or Cytoscape simply hangs for a long time, trying to draw the network. Have you tried to prune your result file? Like, discard any sequence which does not have a similarity of at least XX% to any sequence?

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Hi David, Thanks for your reply.

'Does not work'; Fails to load the network graph. I don't get any errors, to the gui anyway. Also Cytoscape is not hanging, it loads as normal, in good time, but just no output.

I concede that this is quite a big network, and you are probably right I am asking too much from the app. I've pruned as much as I feel comfortable with.

I guess my question is, does anyone know an alternative way of doing this? i've got a very powerful machine, so hopefully this shouldnt be limiting.

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Just to make sure, you do realise that Cytoscape does not visualize very big networks by default, right? You have to right click the network in the left sidebar and choose "Show network" or something similar.

Again, try to prune your dataset. Use CD-HIT to build a non-redundant input set, remove bad BLAST hits etcetc.

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NO! I didnt know that! I've only ever used small networks. Thank you David Westergaard.

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