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To create a network
with weighted edges, we represent the network as a five column
matrix, with the number of rows equal to the number of edges. As an
example we will weight a network constructed by phylogenetic
profiling. In each row the first two cols have the IDs of the paired
orthologs, the third column has a 0 (in this case) since the
connecting edge has no direction, the fourth column is the method ID
(phylogenetic profiling), and the 5th column is the probability that
the profile similarity could have occurred purely by chance. For
this tutorial, we use following data:
COG0001
COG0007 0 M0037 0.427687442686038
COG0001 COG0045 0 M0037 0.323141599227162
COG0001 COG0054 0 M0037 0.317120174092673
COG0001 COG0063 0 M0037 0.262304516458299
COG0001 COG0074 0 M0037 0.323141599227162
COG0001 COG0082 0 M0037 0.35787446628169
COG0001 COG0108 0 M0037 0.317120174092673
COG0001 COG0111 0 M0037 0.262304516458299
COG0669
COG1158 0 M0037 0.390289978866581
COG0669 COG1159 0 M0037 0.605561256310388
COG0669 COG1162 0 M0037 0.290270944130449
COG2190 COG3414 0 M0037 0.403796627789251
COG2190 COG3444 0 M0037 0.337013380698925
COG2190 COG3623 0 M0037 0.305619736118715
COG2190 COG3711 0 M0037 0.403796627789251
COG2190 COG3715 0 M0037 0.337013380698925
COG2190 COG3716 0 M0037 0.337013380698925
COG2190 COG3835 0 M0037 0.275403852766849
COG2190 COG4668 0 M0037 0.492058472821917
COG2190 COG4987 0 M0037 0.270698940335453
COG2190 COG4988 0 M0037 0.294197134509517
COG2191 COG2266 0 M0037 0.257053580945912
COG2191 COG2450 0 M0037 0.317639621878071
COG2191 COG2511 0 M0037 0.257053580945912
COG2191 COG2811 0 M0037 0.434062434523347
COG2191 COG2888 0 M0037 0.257053580945912
COG2191 COG3390 0 M0037 0.304200087240157
COG2191 COG3620 0 M0037 0.304200087240157
COG2191 COG3635 0 M0037 0.318647443121954
Note: You can find a list of method ID in the method table which is available
under View menu. In the same place you can create your
own method if you can not find a suitable one for your data.
Note: For more information about data format, please
reference here.
Note:
If you have a lot of data, you can either copy/paste in several
separate steps, or run VisANT as
application and load the data from a file. |