{"id":408,"date":"2020-07-05T13:29:29","date_gmt":"2020-07-05T05:29:29","guid":{"rendered":"https:\/\/www.next-bioinfo.tw\/?p=408"},"modified":"2024-10-08T15:00:18","modified_gmt":"2024-10-08T07:00:18","slug":"%e3%80%90ngs-%e6%ac%a1%e4%b8%96%e4%bb%a3%e5%9f%ba%e5%9b%a0%e9%ab%94%e8%b3%87%e6%96%99%e7%a7%91%e5%ad%b8%e3%80%91gene2vec%e5%9f%ba%e5%9b%a0%e7%9a%84%e5%88%86%e6%95%a3%e5%bc%8f%e8%a1%a8%e5%be%b5","status":"publish","type":"post","link":"https:\/\/www.next-bioinfo.tw\/en\/2020\/07\/%e3%80%90ngs-%e6%ac%a1%e4%b8%96%e4%bb%a3%e5%9f%ba%e5%9b%a0%e9%ab%94%e8%b3%87%e6%96%99%e7%a7%91%e5%ad%b8%e3%80%91gene2vec%e5%9f%ba%e5%9b%a0%e7%9a%84%e5%88%86%e6%95%a3%e5%bc%8f%e8%a1%a8%e5%be%b5\/","title":{"rendered":"\u3010NGS with Data Science\u3011Gene2vec distributed representation of genes pipeline reproduction"},"content":{"rendered":"<p>This article explains how to use the pipeline in the paper \"Gene2vec: distributed representation of genes based on co-expression.\" and re-train the model with your data.<\/p>\n\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_54_1 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" >Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\" role=\"button\"><label for=\"item-6a6d354c8a7e1\" ><span class=\"\"><span style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input aria-label=\"Toggle\" type=\"checkbox\"  id=\"item-6a6d354c8a7e1\"><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.next-bioinfo.tw\/en\/2020\/07\/%e3%80%90ngs-%e6%ac%a1%e4%b8%96%e4%bb%a3%e5%9f%ba%e5%9b%a0%e9%ab%94%e8%b3%87%e6%96%99%e7%a7%91%e5%ad%b8%e3%80%91gene2vec%e5%9f%ba%e5%9b%a0%e7%9a%84%e5%88%86%e6%95%a3%e5%bc%8f%e8%a1%a8%e5%be%b5\/#%E5%AE%89%E8%A3%9D%E6%B5%81%E7%A8%8B\" title=\"Install pipeline\">Install pipeline<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.next-bioinfo.tw\/en\/2020\/07\/%e3%80%90ngs-%e6%ac%a1%e4%b8%96%e4%bb%a3%e5%9f%ba%e5%9b%a0%e9%ab%94%e8%b3%87%e6%96%99%e7%a7%91%e5%ad%b8%e3%80%91gene2vec%e5%9f%ba%e5%9b%a0%e7%9a%84%e5%88%86%e6%95%a3%e5%bc%8f%e8%a1%a8%e5%be%b5\/#%E8%A8%93%E7%B7%B4%E6%A8%A1%E5%9E%8B\" title=\"Training Models\">Training Models<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.next-bioinfo.tw\/en\/2020\/07\/%e3%80%90ngs-%e6%ac%a1%e4%b8%96%e4%bb%a3%e5%9f%ba%e5%9b%a0%e9%ab%94%e8%b3%87%e6%96%99%e7%a7%91%e5%ad%b8%e3%80%91gene2vec%e5%9f%ba%e5%9b%a0%e7%9a%84%e5%88%86%e6%95%a3%e5%bc%8f%e8%a1%a8%e5%be%b5\/#%E5%8F%83%E8%80%83%E8%B3%87%E6%96%99\" title=\"References\">References<\/a><\/li><\/ul><\/nav><\/div>\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"%E5%AE%89%E8%A3%9D%E6%B5%81%E7%A8%8B\"><\/span>Install pipeline<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>First, we create the path to download the package . We created a conda  virtual environment of Python 3.7 as following commands:<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#d8dee9ff;--cbp-line-number-width:8.4375px;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:10px 0px 10px 16px;margin-bottom:-2px;width:100%;text-align:left;background-color:#39404f;color:#c8d0e0\">Bash<\/span><span role=\"button\" tabindex=\"0\" data-code=\"mkdir gene2vec_testcd gene2vec_test\/conda create -n gene2vec_test_env python=3.7conda activate gene2vec_test_env\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewbox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #88C0D0\">mkdir<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">gene2vec_test<\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">cd<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">gene2vec_test\/<\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">conda<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">create<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-n<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">gene2vec_test_env<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">python=<\/span><span style=\"color: #B48EAD\">3.7<\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">conda<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">activate<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">gene2vec_test_env<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p>Then download the package with git command:<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#d8dee9ff;--cbp-line-number-width:8.4375px;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:10px 0px 10px 16px;margin-bottom:-2px;width:100%;text-align:left;background-color:#39404f;color:#c8d0e0\">Bash<\/span><span role=\"button\" tabindex=\"0\" data-code=\"git clone https:\/\/github.com\/jingcheng-du\/Gene2vec.gitcd Gene2vec\/\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewbox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #88C0D0\">git<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">clone<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">https:\/\/github.com\/jingcheng-du\/Gene2vec.git<\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">cd<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">Gene2vec\/<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p>Because there are differences in parameter names between gensim 3.x and 4, if you want to use gemsim with 3.x version, remember to change requirements.txt: change gensim&gt;=3.4.0 to gensim==3.4.0. (If you want to use gensim with 4.x version you need to modify gene2vec.py, such as changing the \"size\" of the word2vec object to \"vector_size\", etc.)<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#d8dee9ff;--cbp-line-number-width:8.4375px;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:10px 0px 10px 16px;margin-bottom:-2px;width:100%;text-align:left;background-color:#39404f;color:#c8d0e0\">Bash<\/span><span role=\"button\" tabindex=\"0\" data-code=\"pip install -r requirements.txt\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewbox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #88C0D0\">pip<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">install<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-r<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">requirements.txt<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p>After the installation program is completed, we can test it as the command:<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#d8dee9ff;--cbp-line-number-width:8.4375px;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:10px 0px 10px 16px;margin-bottom:-2px;width:100%;text-align:left;background-color:#39404f;color:#c8d0e0\">Bash<\/span><span role=\"button\" tabindex=\"0\" data-code=\"cd src\/python gene2vec.py \" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewbox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #88C0D0\">cd<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">src\/<\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">python<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">gene2vec.py<\/span><span style=\"color: #D8DEE9FF\"> <\/span><\/span>\n<span class=\"line\"><\/span><\/code><\/pre><\/div>\n\n\n\n<p>If the following message appears, the installation should be good.<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#d8dee9ff;--cbp-line-number-width:8.4375px;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:10px 0px 10px 16px;margin-bottom:-2px;width:100%;text-align:left;background-color:#39404f;color:#c8d0e0\">Bash<\/span><span role=\"button\" tabindex=\"0\" data-code=\"usage: gene2vec.py [-h] N [N ...]\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewbox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #88C0D0\">usage:<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">gene2vec.py<\/span><span style=\"color: #D8DEE9FF\"> [-h] N <\/span><span style=\"color: #ECEFF4\">[<\/span><span style=\"color: #D8DEE9FF\">N ...<\/span><span style=\"color: #ECEFF4\">]<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"%E8%A8%93%E7%B7%B4%E6%A8%A1%E5%9E%8B\"><\/span>Training Models<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Then we could use the testing data to run the example :<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#d8dee9ff;--cbp-line-number-width:8.4375px;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:10px 0px 10px 16px;margin-bottom:-2px;width:100%;text-align:left;background-color:#39404f;color:#c8d0e0\">Bash<\/span><span role=\"button\" tabindex=\"0\" data-code=\"python gene2vec.py ..\/data\/ ..\/out txt\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewbox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #88C0D0\">python<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">gene2vec.py<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">..\/data\/<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">..\/out<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">txt<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p>The gene vector would saved at the running path and here were some example data:<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#d8dee9ff;--cbp-line-number-width:8.4375px;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:10px 0px 10px 16px;margin-bottom:-2px;width:100%;text-align:left;background-color:#39404f;color:#c8d0e0\">Bash<\/span><span role=\"button\" tabindex=\"0\" data-code=\"head -n 2 outgene2vec_dim_100_iter_1.txtFGF6\t0.002153057 0.001094015 0.0040485994 0.003507802 -0.0034948308 -0.0032273065 0.002758114 -0.0044576144 0.002355916 0.0017780543 0.004745546 0.0018376901 -0.0035088449 -0.0005739574 -0.000108827386 0.002103943 -0.0038852852 0.0012951874 -0.0031769034 -0.004375249 0.004074314 -0.0026881285 0.004214152 -0.004282877 0.0022233215 0.004169825 0.00061325595 2.0139367e-05 -0.0016913096 0.0025811284 0.0031880501 -0.0019990925 -0.0047910786 0.002188197 0.0026727102 -0.0006805879 0.00019095051 0.0010278132 0.0017754859 0.0031797176 -0.003708027 -0.0043337652 0.0035265626 -0.0008643125 0.00084504695 -0.00054039893 0.0003750502 -0.0037928058 -0.0042927195 -0.0047074244 -0.0017722481 0.00025958134 -0.0026379086 0.00018871028 -0.0019723917 -0.00021585514 0.0033635853 0.0022829815 -0.0024485104 0.0011425553 0.003241704 0.0047381823 0.0012685822 0.0041412427 0.0019761408 0.0019880526 0.0039201365 0.0013327249 -0.002263571 -0.0044547706 0.0037608626 0.00095062394 -0.00030630908 0.0031630904 -0.0018972668 0.004344254 0.0025073248 0.0037321039 -0.004189576 0.0025266777 0.0005846647 0.0019490473 0.0018105969 -0.004199487 0.0020253006 -0.0017606984 -0.004815944 0.0046018823 0.0042982115 0.00051282457 -0.0009345786 0.003392324 -0.0032844574 0.0011845101 -0.0011895953 -0.0012602699 -0.00042309787 0.004582391 0.0025786795 -0.0024350516 GFI1B\t-0.0029350498 0.0043180487 -0.004318311 0.0019120751 -0.0038370104 -0.00023128637 -0.004420749 -0.0035758333 -0.0040116534 0.0012707855 -0.0009630754 0.0004477923 0.0020208724 -0.00041648198 0.003939566 -0.0040858993 -0.004756729 0.0018472039 -0.0021072265 0.002428173 -0.00014559152 0.0045682737 -0.0033070655 -0.0035072211 0.00053472363 -0.0026147643 0.00052187295 0.0034156216 -0.0035089792 0.001963524 -0.0040159533 0.0029510746 0.004897053 0.0017880275 0.0009832341 -0.004501591 -0.0021778357 0.002407189 0.000616764 -0.003227798 -0.0042902012 0.0024847183 0.003374102 0.002082069 0.001478934 0.0048288074 0.0042617135 -0.0018422379 0.0039390987 0.00026498176 -0.00028904268 0.0011463418 0.0027650178 0.0037835115 0.0007013022 0.004905474 0.0006962089 0.0002940799 0.0038201583 -0.0031658853 -0.00292867 -0.00054527074 0.004884007 0.002188833 0.00015647558 -0.002252723 0.0020673836 0.0038181976 0.00041569016 -0.003276892 -0.002797324 0.0020927635 0.0010414731 -0.004298761 0.002510277 -0.0017390802 0.00439754 -0.0042876415 -0.00071369467 0.002830168 -0.0037963414 0.0036242604 0.00023945107 0.004529737 0.001412234 -0.0010020512 0.0044706156 0.0015063612 0.0029264004 -0.0043842485 -0.0016326424 0.0022118944 0.00042738195 -0.004558031 -0.003733534 -0.0029223813 0.0048098615 -0.0019367941 0.00491898 -0.0025868856 \" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewbox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #88C0D0\">head<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-n<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">2<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">outgene2vec_dim_100_iter_1.txt<\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">FGF6<\/span><span style=\"color: #D8DEE9FF\">\t<\/span><span style=\"color: #B48EAD\">0.002153057<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.001094015<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0040485994<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.003507802<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0034948308<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0032273065<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.002758114<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0044576144<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.002355916<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0017780543<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.004745546<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0018376901<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0035088449<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0005739574<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.000108827386<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.002103943<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0038852852<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0012951874<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0031769034<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.004375249<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.004074314<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0026881285<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.004214152<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.004282877<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0022233215<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.004169825<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00061325595<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">2.0139367<\/span><span style=\"color: #A3BE8C\">e-05<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0016913096<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0025811284<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0031880501<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0019990925<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0047910786<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.002188197<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0026727102<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0006805879<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00019095051<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0010278132<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0017754859<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0031797176<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.003708027<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0043337652<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0035265626<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0008643125<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00084504695<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.00054039893<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0003750502<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0037928058<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0042927195<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0047074244<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0017722481<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00025958134<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0026379086<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00018871028<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0019723917<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.00021585514<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0033635853<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0022829815<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0024485104<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0011425553<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.003241704<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0047381823<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0012685822<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0041412427<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0019761408<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0019880526<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0039201365<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0013327249<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.002263571<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0044547706<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0037608626<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00095062394<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.00030630908<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0031630904<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0018972668<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.004344254<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0025073248<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0037321039<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.004189576<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0025266777<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0005846647<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0019490473<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0018105969<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.004199487<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0020253006<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0017606984<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.004815944<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0046018823<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0042982115<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00051282457<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0009345786<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.003392324<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0032844574<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0011845101<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0011895953<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0012602699<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.00042309787<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.004582391<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0025786795<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0024350516<\/span><span style=\"color: #D8DEE9FF\"> <\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">GFI1B<\/span><span style=\"color: #D8DEE9FF\">\t<\/span><span style=\"color: #A3BE8C\">-0.0029350498<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0043180487<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.004318311<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0019120751<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0038370104<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.00023128637<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.004420749<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0035758333<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0040116534<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0012707855<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0009630754<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0004477923<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0020208724<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.00041648198<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.003939566<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0040858993<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.004756729<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0018472039<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0021072265<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.002428173<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.00014559152<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0045682737<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0033070655<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0035072211<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00053472363<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0026147643<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00052187295<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0034156216<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0035089792<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.001963524<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0040159533<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0029510746<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.004897053<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0017880275<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0009832341<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.004501591<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0021778357<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.002407189<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.000616764<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.003227798<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0042902012<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0024847183<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.003374102<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.002082069<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.001478934<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0048288074<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0042617135<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0018422379<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0039390987<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00026498176<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.00028904268<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0011463418<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0027650178<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0037835115<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0007013022<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.004905474<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0006962089<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0002940799<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0038201583<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0031658853<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.00292867<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.00054527074<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.004884007<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.002188833<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00015647558<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.002252723<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0020673836<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0038181976<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00041569016<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.003276892<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.002797324<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0020927635<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0010414731<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.004298761<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.002510277<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0017390802<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00439754<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0042876415<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.00071369467<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.002830168<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0037963414<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0036242604<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00023945107<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.004529737<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.001412234<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0010020512<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0044706156<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0015063612<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0029264004<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0043842485<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0016326424<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0022118944<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00042738195<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.004558031<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.003733534<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0029223813<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.0048098615<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0019367941<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0.00491898<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-0.0025868856<\/span><span style=\"color: #D8DEE9FF\"> <\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p>In addition, we could use the pre-trained model and run the tSNE, for example:<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#d8dee9ff;--cbp-line-number-width:8.4375px;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:10px 0px 10px 16px;margin-bottom:-2px;width:100%;text-align:left;background-color:#39404f;color:#c8d0e0\">Bash<\/span><span role=\"button\" tabindex=\"0\" data-code=\"pip install MulticoreTSNEpip  install scikit-learnpython tsne_multi_core.py\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewbox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #88C0D0\">pip<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">install<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">MulticoreTSNE<\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">pip<\/span><span style=\"color: #D8DEE9FF\">  <\/span><span style=\"color: #A3BE8C\">install<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">scikit-learn<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">python<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">tsne_multi_core.py<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p>and use plot.py to plot it :<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#d8dee9ff;--cbp-line-number-width:8.4375px;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:10px 0px 10px 16px;margin-bottom:-2px;width:100%;text-align:left;background-color:#39404f;color:#c8d0e0\">Python<\/span><span role=\"button\" tabindex=\"0\" data-code=\"import pandas as pdimport matplotlib.pyplot as pltplt.style.use('ggplot')df=pd.read_csv(&quot;TSNE_data_gene2vec.txt_100.txt&quot;,sep=&quot; &quot;,header=None)df.columns = ['x', 'y']plt.scatter(x=df[&quot;x&quot;],y=df[&quot;y&quot;])plt.show()\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewbox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #81A1C1\">import<\/span><span style=\"color: #D8DEE9FF\"> pandas <\/span><span style=\"color: #81A1C1\">as<\/span><span style=\"color: #D8DEE9FF\"> pd<\/span><\/span>\n<span class=\"line\"><span style=\"color: #81A1C1\">import<\/span><span style=\"color: #D8DEE9FF\"> matplotlib<\/span><span style=\"color: #ECEFF4\">.<\/span><span style=\"color: #D8DEE9FF\">pyplot <\/span><span style=\"color: #81A1C1\">as<\/span><span style=\"color: #D8DEE9FF\"> plt<\/span><\/span>\n<span class=\"line\"><span style=\"color: #D8DEE9FF\">plt<\/span><span style=\"color: #ECEFF4\">.<\/span><span style=\"color: #D8DEE9FF\">style<\/span><span style=\"color: #ECEFF4\">.<\/span><span style=\"color: #88C0D0\">use<\/span><span style=\"color: #ECEFF4\">(<\/span><span style=\"color: #ECEFF4\">&#39;<\/span><span style=\"color: #A3BE8C\">ggplot<\/span><span style=\"color: #ECEFF4\">&#39;<\/span><span style=\"color: #ECEFF4\">)<\/span><\/span>\n<span class=\"line\"><span style=\"color: #D8DEE9FF\">df<\/span><span style=\"color: #81A1C1\">=<\/span><span style=\"color: #D8DEE9FF\">pd<\/span><span style=\"color: #ECEFF4\">.<\/span><span style=\"color: #88C0D0\">read_csv<\/span><span style=\"color: #ECEFF4\">(<\/span><span style=\"color: #ECEFF4\">&quot;<\/span><span style=\"color: #A3BE8C\">TSNE_data_gene2vec.txt_100.txt<\/span><span style=\"color: #ECEFF4\">&quot;<\/span><span style=\"color: #ECEFF4\">,<\/span><span style=\"color: #D8DEE9\">sep<\/span><span style=\"color: #81A1C1\">=<\/span><span style=\"color: #ECEFF4\">&quot;<\/span><span style=\"color: #A3BE8C\"> <\/span><span style=\"color: #ECEFF4\">&quot;<\/span><span style=\"color: #ECEFF4\">,<\/span><span style=\"color: #D8DEE9\">header<\/span><span style=\"color: #81A1C1\">=None<\/span><span style=\"color: #ECEFF4\">)<\/span><\/span>\n<span class=\"line\"><span style=\"color: #D8DEE9FF\">df<\/span><span style=\"color: #ECEFF4\">.<\/span><span style=\"color: #D8DEE9FF\">columns <\/span><span style=\"color: #81A1C1\">=<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #ECEFF4\">[<\/span><span style=\"color: #ECEFF4\">&#39;<\/span><span style=\"color: #A3BE8C\">x<\/span><span style=\"color: #ECEFF4\">&#39;<\/span><span style=\"color: #ECEFF4\">,<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #ECEFF4\">&#39;<\/span><span style=\"color: #A3BE8C\">y<\/span><span style=\"color: #ECEFF4\">&#39;<\/span><span style=\"color: #ECEFF4\">]<\/span><\/span>\n<span class=\"line\"><span style=\"color: #D8DEE9FF\">plt<\/span><span style=\"color: #ECEFF4\">.<\/span><span style=\"color: #88C0D0\">scatter<\/span><span style=\"color: #ECEFF4\">(<\/span><span style=\"color: #D8DEE9\">x<\/span><span style=\"color: #81A1C1\">=<\/span><span style=\"color: #D8DEE9FF\">df<\/span><span style=\"color: #ECEFF4\">[<\/span><span style=\"color: #ECEFF4\">&quot;<\/span><span style=\"color: #A3BE8C\">x<\/span><span style=\"color: #ECEFF4\">&quot;<\/span><span style=\"color: #ECEFF4\">],<\/span><span style=\"color: #D8DEE9\">y<\/span><span style=\"color: #81A1C1\">=<\/span><span style=\"color: #D8DEE9FF\">df<\/span><span style=\"color: #ECEFF4\">[<\/span><span style=\"color: #ECEFF4\">&quot;<\/span><span style=\"color: #A3BE8C\">y<\/span><span style=\"color: #ECEFF4\">&quot;<\/span><span style=\"color: #ECEFF4\">])<\/span><\/span>\n<span class=\"line\"><span style=\"color: #D8DEE9FF\">plt<\/span><span style=\"color: #ECEFF4\">.<\/span><span style=\"color: #88C0D0\">show<\/span><span style=\"color: #ECEFF4\">()<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p>than could get the 2d projection  of the genes.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img decoding=\"async\" width=\"640\" height=\"480\" src=\"https:\/\/ml4fi34j3t2e.i.optimole.com\/w:auto\/h:auto\/q:mauto\/f:avif\/https:\/\/www.next-bioinfo.tw\/wp-content\/uploads\/2024\/10\/Figure_1.png\" alt=\"\" class=\"wp-image-411\" style=\"aspect-ratio:1.3333333333333333;width:424px;height:auto\"\/><\/figure>\n\n\n\n<p>Each data point was the representation of a gene. Now, we have roughly completed the conversion of gene names to vectors for decentralized representation. This method can enhance the prediction capabilities of other biological markers .<\/p>\n\n\n\n<p>If we trace the source code of gene2vec.py,  can see that the training method is similar to the general NLP word vector method. The idea was only to change the general NLP input to the gene list of the GSEA data set.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"%E5%8F%83%E8%80%83%E8%B3%87%E6%96%99\"><\/span>References<span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<ul>\n<li>Du, J., Jia, P., Dai, Y. <em>et al.<\/em> Gene2vec: distributed representation of genes based on co-expression. <em>BMC Genomics<\/em> 20 (Suppl 1), 82 (2019). https:\/\/doi.org\/10.1186\/s12864-018-5370-x<\/li>\n<\/ul>","protected":false},"excerpt":{"rendered":"<p>\u9019\u88e1\u7d00\u9304\u5982\u4f55\u5229\u7528\u8ad6\u6587Gene2vec\u63d0\u4f9b\u7684\u7a0b\u5f0f\uff0c\u4e26\u642d\u914d\u81ea\u5df1\u7684\u8cc7\u6599\u91cd\u65b0\u8a13\u7df4\u6a21\u578b\uff0c\u8a13\u7df4\u57fa\u56e0\u7684\u5206\u6563\u5f0f\u8868\u5fb5<\/p>","protected":false},"author":1,"featured_media":249,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"site-container-style":"default","site-container-layout":"default","site-sidebar-layout":"default","site-transparent-header":"default","disable-article-header":"default","disable-site-header":"default","disable-site-footer":"default","disable-content-area-spacing":"default","footnotes":""},"categories":[2],"tags":[59,57,58],"_links":{"self":[{"href":"https:\/\/www.next-bioinfo.tw\/en\/wp-json\/wp\/v2\/posts\/408"}],"collection":[{"href":"https:\/\/www.next-bioinfo.tw\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.next-bioinfo.tw\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.next-bioinfo.tw\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.next-bioinfo.tw\/en\/wp-json\/wp\/v2\/comments?post=408"}],"version-history":[{"count":5,"href":"https:\/\/www.next-bioinfo.tw\/en\/wp-json\/wp\/v2\/posts\/408\/revisions"}],"predecessor-version":[{"id":414,"href":"https:\/\/www.next-bioinfo.tw\/en\/wp-json\/wp\/v2\/posts\/408\/revisions\/414"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.next-bioinfo.tw\/en\/wp-json\/wp\/v2\/media\/249"}],"wp:attachment":[{"href":"https:\/\/www.next-bioinfo.tw\/en\/wp-json\/wp\/v2\/media?parent=408"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.next-bioinfo.tw\/en\/wp-json\/wp\/v2\/categories?post=408"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.next-bioinfo.tw\/en\/wp-json\/wp\/v2\/tags?post=408"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}