text: user8601: What are some good tools (in Python if possible) for creating gene co-expression networks from RNA seq data?
  
  user8601: After looking around, it seems like the Camoco library is suitable. 
  
  user8749: it depends on the size of your data. If you have enough RAM available, then you may directly compute a correlation-based distance matrix using the cor() function (with method="spearman" or method="pearson"). But you may also give a try to Mutual Information distance using the Parmigene (https://cran.r-project.org/web/packages/parmigene/index.html) R package or partial correlations with the Corpcor (https://cran.r-project.org/web/packages/corpcor/index.html) R package.
  If you have a large expression matrix, remember to use the excellent data.table package and its fread() function.
  
original_text: 8601: <p>What are some good tools (in Python if possible) for creating gene co-expression networks from RNA seq data?</p>
   8601: <p>After looking around, it seems like the <a href="https://camoco.readthedocs.io/en/latest/index.html" rel="nofollow noreferrer">Camoco library</a> is suitable. </p>
   8749: <p>it depends on the size of your data. If you have enough RAM available, then you may directly compute a correlation-based distance matrix using the <em>cor()</em> function (with method="spearman" or method="pearson"). But you may also give a try to Mutual Information distance using the <strong>Parmigene</strong> (<a href="https://cran.r-project.org/web/packages/parmigene/index.html" rel="nofollow noreferrer">https://cran.r-project.org/web/packages/parmigene/index.html</a>) R package or partial correlations with the <strong>Corpcor</strong> (<a href="https://cran.r-project.org/web/packages/corpcor/index.html" rel="nofollow noreferrer">https://cran.r-project.org/web/packages/corpcor/index.html</a>) R package.
  If you have a large expression matrix, remember to use the excellent <strong>data.table</strong> package and its <em>fread()</em> function.</p>
  