{"id":7105,"date":"2013-11-12T11:47:28","date_gmt":"2013-11-12T09:47:28","guid":{"rendered":"http:\/\/www.ehu.es\/sgi\/?p=7105"},"modified":"2015-11-04T11:20:06","modified_gmt":"2015-11-04T09:20:06","slug":"trinity-3","status":"publish","type":"post","link":"https:\/\/www.ehu.eus\/sgi\/scientific-software\/trinity-3","title":{"rendered":"Trinity"},"content":{"rendered":"<h1>General information<\/h1>\n<p>2.1.1 release. Trinity, represents a novel method for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data. Trinity combines three independent software modules: Inchworm, Chrysalis, and Butterfly, applied sequentially to process large volumes of RNA-seq reads. Trinity partitions the sequence data into many individual de Bruijn graphs, each representing the transcriptional complexity at at a given gene or locus, and then processes each graph independently to extract full-length splicing isoforms and to tease apart transcripts derived from paralogous genes. Briefly, the process works like so:<\/p>\n<ul>\n<li><strong>Inchworm<\/strong> assembles the RNA-seq data into the unique sequences of transcripts, often generating full-length transcripts for a dominant isoform, but then reports just the unique portions of alternatively spliced transcripts.<\/li>\n<\/ul>\n<ul>\n<li><strong>Chrysalis<\/strong> clusters the Inchworm contigs into clusters and constructs complete de Bruijn graphs for each cluster. Each cluster represents the full transcriptonal complexity for a given gene (or sets of genes that share sequences in common). Chrysalis then partitions the full read set among these disjoint graphs.<\/li>\n<\/ul>\n<ul>\n<li><strong>Butterfly<\/strong> then processes the individual graphs in parallel, tracing the paths that reads and pairs of reads take within the graph, ultimately reporting full-length transcripts for alternatively spliced isoforms, and teasing apart transcripts that corresponds to paralogous genes.<\/li>\n<\/ul>\n<h1>How to use<\/h1>\n<p>You can use the<\/p>\n<pre>send_trinity<\/pre>\n<p>command to submit jobs to the queue system. After answering few questions a script will be created and submitted to the queue system. For advanced users it can be used to generate a sample script.<\/p>\n<h1>Performance<\/h1>\n<p>Trinity can be run in parallel but it is not very efficient above 4 cores with low performance, as can be seen in the the table. Trinity consumes high amounts of RAM.<\/p>\n<table border=\"0\" align=\"center\">\n<caption>Performance of Trinity<\/caption>\n<tbody>\n<tr>\n<td>Cores<\/td>\n<td align=\"right\">\u00a01<\/td>\n<td align=\"right\">4<\/td>\n<td align=\"right\">8<\/td>\n<td align=\"right\">12<\/td>\n<\/tr>\n<tr>\n<td>Time<\/td>\n<td align=\"right\">5189<\/td>\n<td align=\"right\">2116<\/td>\n<td align=\"right\">1754<\/td>\n<td align=\"right\">1852<\/td>\n<\/tr>\n<tr>\n<td>Speddup<\/td>\n<td align=\"right\">1<\/td>\n<td align=\"right\">2.45<\/td>\n<td align=\"right\">2.96<\/td>\n<td align=\"right\">2.80<\/td>\n<\/tr>\n<tr>\n<td>Efficiency (%)<\/td>\n<td align=\"right\">\u00a0100<\/td>\n<td align=\"right\">61<\/td>\n<td align=\"right\">37<\/td>\n<td align=\"right\">23<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>&nbsp;<\/p>\n<h1>More information<\/h1>\n<p><a title=\"Trinity home page\" href=\"http:\/\/trinityrnaseq.sourceforge.net\/\" target=\"_blank\">Trinity web page<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>General information 2.1.1 release. Trinity, represents a novel method for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data. Trinity combines three independent software modules: Inchworm, Chrysalis, and Butterfly, applied sequentially to process large volumes of RNA-seq reads. Trinity partitions the sequence data into many individual de Bruijn graphs, each representing the &hellip; <a href=\"https:\/\/www.ehu.eus\/sgi\/scientific-software\/trinity-3\" class=\"more-link\">Seguir leyendo <span class=\"screen-reader-text\">Trinity<\/span> <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_links_to":"","_links_to_target":""},"categories":[239,196],"tags":[],"_links":{"self":[{"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/posts\/7105"}],"collection":[{"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/comments?post=7105"}],"version-history":[{"count":4,"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/posts\/7105\/revisions"}],"predecessor-version":[{"id":8213,"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/posts\/7105\/revisions\/8213"}],"wp:attachment":[{"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/media?parent=7105"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/categories?post=7105"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/tags?post=7105"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}