{"id":7113,"date":"2013-11-12T11:44:17","date_gmt":"2013-11-12T09:44:17","guid":{"rendered":"http:\/\/www.ehu.es\/sgi\/?p=7113"},"modified":"2015-11-04T11:20:59","modified_gmt":"2015-11-04T09:20:59","slug":"trinity","status":"publish","type":"post","link":"https:\/\/www.ehu.eus\/sgi\/kalkulu-softwarea\/trinity","title":{"rendered":"Trinity"},"content":{"rendered":"<h1>Informaci\u00f3n general<\/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>Nola erabili<\/h1>\n<pre>send_trinity<\/pre>\n<p>komandoa erabili daiteke lanak koletara bidaltzeko. Galdera batzuk erantzun eta gero koletara bidali behar den scripta sortu eta bidaliko du. Erabiltzaile\u00a0 aurreratuentzak erabili daiteke ere adibide scrtip bat sortzeko.<\/p>\n<h1>Errendimendua<\/h1>\n<p>Trinity paraleloan exekutatu daiteke baina errendimendu txarrarekin 4 koretik gora, nahiz eta kore kopurua asko igo kalkulu denbora ez da asko jaisten. Trinimyk RAM asko erabiltzen du.<\/p>\n<table border=\"0\" align=\"center\">\n<caption>Trinityren errendimendua<\/caption>\n<tbody>\n<tr>\n<td>Koreak<\/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>Denbora<\/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>Azelerazioa<\/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>Eraginkortasuna (%)<\/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>Informazio gehiago<\/h1>\n<p><a title=\"Trinity home page\" href=\"http:\/\/trinityrnaseq.sourceforge.net\/\" target=\"_blank\">P\u00e1gina web de Trinity<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Informaci\u00f3n general 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\/kalkulu-softwarea\/trinity\" 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":[178,66],"tags":[],"_links":{"self":[{"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/posts\/7113"}],"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=7113"}],"version-history":[{"count":2,"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/posts\/7113\/revisions"}],"predecessor-version":[{"id":8215,"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/posts\/7113\/revisions\/8215"}],"wp:attachment":[{"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/media?parent=7113"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/categories?post=7113"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.ehu.eus\/sgi\/wp-json\/wp\/v2\/tags?post=7113"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}