{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T05:10:08Z","timestamp":1772169008885,"version":"3.50.1"},"reference-count":22,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2015,8,5]],"date-time":"2015-08-05T00:00:00Z","timestamp":1438732800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["f1000research.com"],"crossmark-restriction":false},"short-container-title":["F1000Res"],"abstract":"<ns4:p>iCTNet (integrated Complex Traits Networks) version 2 is a Cytoscape app and database that allows researchers to build heterogeneous networks by integrating a variety of biological interactions, thus offering a systems-level view of human complex traits. iCTNet2 is built from a variety of large-scale biological datasets, collected from public repositories to facilitate the building, 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Approved with reservations","URL":"https:\/\/f1000research.com\/articles\/4-485\/v1#article-reports","order":0,"name":"referee-status","label":"Referee status","group":{"name":"current-referee-status","label":"Current Referee Status"}},{"value":"10.5256\/f1000research.7350.r9869, Amitabh Sharma, Department of Medicine, Harvard Medical Center, Boston, MA, USA, 24 Aug 2015, version 1, 1 approved, 1 approved with reservations","URL":"https:\/\/f1000research.com\/articles\/4-485\/v1#referee-response-9869","order":0,"name":"referee-response-9869","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.5256\/f1000research.7350.r9868, Gary D. Bader, Department of Computer Science, University of Toronto, Toronto, ON, Canada, 02 Sep 2015, version 1, 1 approved, 1 approved with reservations","URL":"https:\/\/f1000research.com\/articles\/4-485\/v1#referee-response-9868","order":1,"name":"referee-response-9868","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Sergio Baranzini<\/b>; \n<i>Posted: 19 Sep 2015<\/i>; Thank you for your comments!Please see a point-by point answer below\n<b>Major points:P5 \u201cNext, a case study is presented starting with the network from disease nodes as an example.\u201d It would be useful to describe the full workflow, including the scientific question, rationale and end goal.<\/b>This has been added to the revised manuscript\n<b>There is a \u201cCreate similarity network\u201d feature present in the App menu, but this is not described in the manuscript. It would be useful to add a section describing the feature and a use case.<\/b>&nbsp;We have expanded the manuscript to describe this feature in detail and have modified Figure 3 to include an example of this feature.&nbsp;If the user loads too much data, the app will take a long time to respond and the process can\u2019t easily be canceled. The user should be warned in the manuscript or via the app that large queries may take a long time.&nbsp;We have introduced a warning message for large networks. Specifically, the message will be shown if:&nbsp;(1) the size of query diseases &gt; 50 and PPI depth&gt;0; or the size of&nbsp;query diseases &gt; 100;(2) the size of query genes &gt;500 and PPI depth &gt;0; or the size of query&nbsp;genes &gt; 1000;(3) the size of query drugs &gt; 100 and PPI depth &gt;0; or the size of query&nbsp;drugs &gt; 200;\n<b>Search starting points can be gene, disease or drug. Why can\u2019t users search by other starting points e.g. tissue?<\/b>&nbsp;Technically, this should be possible. however, with the three provided starting points, all other searches are technically possible using basic Cytoscape functions.&nbsp;\n<b>The last update date of the ICT database and the date and version used for each resource should be clearly communicated to the user e.g. via the manuscript, app and\/or ICT website.<\/b>&nbsp;Table 1 has been updated.\n<b>Minor points:Page 2: clarify \u201cstacked onto\u201d.<\/b>&nbsp;done\n<b>P2: \u201cids\u201d -&gt; identifiers<\/b>&nbsp;done\n<b>P3: \u201cThe CTD (12)\u201d \u2013 what does \u2018(12)\u2019 mean?<\/b>&nbsp;removed (12)\n<b>P3 \u2013 drugs paragraph. This section is a bit unclear. CTD provides references to drugbank identifiers? Should it be that CTD provides references to drugbank records?&nbsp; How is the \u2018function\u2019 of drugs defined \u2013 is this just the drug target?&nbsp; Drugbank contains fewer entries compared to what?<\/b>&nbsp;This paragraph has been re-written\n<b>P3 \u2013 \u201cphenotype-gene\u201d section.&nbsp; \u201cTo convert from SNP to gene associations, we combined overlapping loci for each GWAS Catalog disease17.\u201d&nbsp; How were the loci combined?<\/b>We have provided a reference detailing how this was done. Basically, we proceeded as follows:Lead-SNPs were assigned windows\u2014regions wherein the causal SNPs are assumed to lie\u2014retrieved from the DAPPLE server. Windows were calculated for each lead-SNP by finding the furthest upstream and downstream SNPs where&nbsp;\n<i>r<\/i>2&nbsp;&gt; 0.5 and extending outwards to the next recombination hotspot. Associations were ordered by confidence, sorting on following criteria: high\/low confidence, p-value (low to high), and recency. In order of confidence, associations were overlapped by their windows into disease-specific loci. By organizing associations into loci, associations from multiple studies tagging the same underlying signal were condensed.\n<b>\u201cThe mode author reported gene for each loci was selected as primary.\u201d \u2013 what is a mode?<\/b>Corrected\n<b>Page 3 and 4 \u2013 in the \u201cTypes of interactions\u201d section, all sub-sections should include the number of interactions e.g. how many gene-tissue interactions are there?<\/b>The numbers of interactions are now specified.\n<b>P5 \u2013 what is a metagraph?<\/b>We refer to a metagraph as the graph describing the interactions among the different node types.\n<b>P5 \u2013 \u201cspike\u201d -&gt; \u201cspoke\u201d?<\/b>&nbsp;done\n<b>P5 \u2013 \u201cUsing standard Cytoscape procedures, we further filtered this network to obtain only the protein interactome associated with more than one autoimmune disease (Figure 3B)\u201d \u2013 the Cytoscape procedures should be detailed to make it easier for users to replicate the results in the manuscript.<\/b>Done\n<b>Figure 1 \u2013 the tissues circle of nodes is covered by edges from other circles \u2013 can it be moved out a bit to show how it connects to other circles?<\/b>Done","URL":"https:\/\/f1000research.com\/articles\/4-485\/v1#referee-comment-1610","order":2,"name":"referee-comment-1610","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"This work was supported from grants from the National Multiple sclerosis Society (AN085369) and the National Institutes of Health (R01NS088155) to SEB. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","order":3,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","order":0,"name":"copyright-info","label":"Copyright"}]}}