{"action":"closed","issue":{"url":"https://api.github.com/repos/kdahlquist/GRNmap/issues/328","repository_url":"https://api.github.com/repos/kdahlquist/GRNmap","labels_url":"https://api.github.com/repos/kdahlquist/GRNmap/issues/328/labels{/name}","comments_url":"https://api.github.com/repos/kdahlquist/GRNmap/issues/328/comments","events_url":"https://api.github.com/repos/kdahlquist/GRNmap/issues/328/events","html_url":"https://github.com/kdahlquist/GRNmap/issues/328","id":208334980,"number":328,"title":"Compute weighted in-, out-, and total-degree for db-derived networks","user":{"login":"kdahlquist","id":6463867,"avatar_url":"https://avatars2.githubusercontent.com/u/6463867?v=3","gravatar_id":"","url":"https://api.github.com/users/kdahlquist","html_url":"https://github.com/kdahlquist","followers_url":"https://api.github.com/users/kdahlquist/followers","following_url":"https://api.github.com/users/kdahlquist/following{/other_user}","gists_url":"https://api.github.com/users/kdahlquist/gists{/gist_id}","starred_url":"https://api.github.com/users/kdahlquist/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/kdahlquist/subscriptions","organizations_url":"https://api.github.com/users/kdahlquist/orgs","repos_url":"https://api.github.com/users/kdahlquist/repos","events_url":"https://api.github.com/users/kdahlquist/events{/privacy}","received_events_url":"https://api.github.com/users/kdahlquist/received_events","type":"User","site_admin":false},"labels":[{"id":136368125,"url":"https://api.github.com/repos/kdahlquist/GRNmap/labels/data%20analysis","name":"data analysis","color":"d4c5f9","default":false},{"id":130673230,"url":"https://api.github.com/repos/kdahlquist/GRNmap/labels/priority%200","name":"priority 0","color":"f7c6c7","default":false}],"state":"closed","locked":false,"assignee":{"login":"maggie-oneil","id":16584287,"avatar_url":"https://avatars1.githubusercontent.com/u/16584287?v=3","gravatar_id":"","url":"https://api.github.com/users/maggie-oneil","html_url":"https://github.com/maggie-oneil","followers_url":"https://api.github.com/users/maggie-oneil/followers","following_url":"https://api.github.com/users/maggie-oneil/following{/other_user}","gists_url":"https://api.github.com/users/maggie-oneil/gists{/gist_id}","starred_url":"https://api.github.com/users/maggie-oneil/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/maggie-oneil/subscriptions","organizations_url":"https://api.github.com/users/maggie-oneil/orgs","repos_url":"https://api.github.com/users/maggie-oneil/repos","events_url":"https://api.github.com/users/maggie-oneil/events{/privacy}","received_events_url":"https://api.github.com/users/maggie-oneil/received_events","type":"User","site_admin":false},"assignees":[{"login":"maggie-oneil","id":16584287,"avatar_url":"https://avatars1.githubusercontent.com/u/16584287?v=3","gravatar_id":"","url":"https://api.github.com/users/maggie-oneil","html_url":"https://github.com/maggie-oneil","followers_url":"https://api.github.com/users/maggie-oneil/followers","following_url":"https://api.github.com/users/maggie-oneil/following{/other_user}","gists_url":"https://api.github.com/users/maggie-oneil/gists{/gist_id}","starred_url":"https://api.github.com/users/maggie-oneil/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/maggie-oneil/subscriptions","organizations_url":"https://api.github.com/users/maggie-oneil/orgs","repos_url":"https://api.github.com/users/maggie-oneil/repos","events_url":"https://api.github.com/users/maggie-oneil/events{/privacy}","received_events_url":"https://api.github.com/users/maggie-oneil/received_events","type":"User","site_admin":false}],"milestone":null,"comments":6,"created_at":"2017-02-17T04:45:30Z","updated_at":"2017-04-27T23:59:12Z","closed_at":"2017-04-27T23:59:12Z","body":"Instead of using Gephi to compute weigted degree stats, we can easily do it in Excel by summing across the rows and columns of the \"network_optimized_weights\" sheet.  This is priority 0.5.\r\n\r\nIn Excel we can also compute the average, median, max, min of weights across the rows and columns to get the descriptive stats for all incoming and outgoing edges for a gene."}}
{"actor":{"display_login":"kdahlquist"}}