I had a table of genes (functions) and OTUs across samples. I read that computing the correlations between these OTUs and genes is a way to assign genes to OTUs. That's what I did, I get a table like this (I selected the correlations above 0.9) :
60 OTU0112 OTU4550 0.928 61 OTU0127 OTU4550 0.917 62 OTU0132 OTU4550 0.903 63 OTU0004 OTU4554 0.914 64 OTU0112 OTU4554 0.912 65 OTU0132 OTU4554 0.904 66 OTU4550 OTU4554 0.938 67 OTU4814 OTU4815 0.905 68 K00013 K00029 0.940 69 K00024 K00031 0.917 70 K00024 K00052 0.947
Then, I want to plot this table with
igraph . I have two questions :
- my table is very huge, I only show a small part : is it meaningful to create a network with a very huge table? And if yes, does igraph is enough powerful for that?
- if it works, I will get OTUs (which will represent main nodes) with genes "around" these OTUs. Is it right to say "if K00024 is close to OTU4554, so the gene K00024 belongs to the OTU4554?"