{"id":19443,"date":"2022-11-06T18:13:01","date_gmt":"2022-11-06T12:43:01","guid":{"rendered":"https:\/\/jassweb.com\/solved\/solved-sum-lines-with-similar-substring-closed\/"},"modified":"2022-11-06T18:13:01","modified_gmt":"2022-11-06T12:43:01","slug":"solved-sum-lines-with-similar-substring-closed","status":"publish","type":"post","link":"https:\/\/jassweb.com\/solved\/solved-sum-lines-with-similar-substring-closed\/","title":{"rendered":"[Solved] sum lines with similar substring [closed]"},"content":{"rendered":"<p> [ad_1]<br \/>\n<\/p>\n<div id=\"answer-32181717\" class=\"answer js-answer accepted-answer js-accepted-answer\" data-answerid=\"32181717\" data-parentid=\"32181677\" data-score=\"2\" data-position-on-page=\"1\" data-highest-scored=\"1\" data-question-has-accepted-highest-score=\"1\" itemprop=\"acceptedAnswer\" itemscope itemtype=\"https:\/\/schema.org\/Answer\">\n<div class=\"post-layout\">\n<div class=\"votecell post-layout--left\"><\/div>\n<div class=\"answercell post-layout--right\">\n<div class=\"s-prose js-post-body\" itemprop=\"text\">\n<p>We could match the substring starting from <code>_<\/code> to the end of the string (<code>.*$<\/code>) in &#8216;IsomiR&#8217; column and replace with <code>''<\/code> using <code>sub<\/code>.  We use that as the grouping variable.  If we are doing this with <code>dplyr<\/code>, the <code>summarise_each<\/code> can be used for <code>sum<\/code>ming multiple columns.<\/p>\n<pre><code>library(dplyr)\ndf1 %&gt;%\n   group_by(IsomiR= sub('_.*$', '', IsomiR)) %&gt;%\n   summarise_each(funs(sum))\n#         IsomiR X185R X68G X60G X134G X124R\n#1 hsa-let-7a-3p     6   11    4    15    10\n#2 hsa-let-7b-3p    28   14   18    57    38\n#3 hsa-let-7c-3p   125   34  106   138    81\n<\/code><\/pre>\n<p>Or we can use <code>separate<\/code> from <code>tidyr<\/code> where we split the &#8216;IsomiR&#8217; column into by specifying the <code>sep='_'<\/code>, use that as grouping variable, and in the <code>summarise_each<\/code> we can <code>select<\/code> the columns using regex pattern in the <code>matches<\/code><\/p>\n<pre><code>library(tidyr)\nseparate(df1, IsomiR, into=c('IsomiR', 'unWanted'), sep='_') %&gt;%\n             group_by(IsomiR) %&gt;%\n             summarise_each(funs(sum), matches('[0-9]+[A-Z]$'))\n<\/code><\/pre>\n<hr>\n<p>Using data.table, we convert the &#8216;data.frame&#8217; to &#8216;data.table&#8217; (<code>setDT(df1)<\/code>).  Remove the substring in &#8216;IsomiR&#8217; with <code>sub<\/code>, use that as a grouping variable, loop through the columns (<code>lapply(.SD, ..)<\/code>) and get the <code>sum<\/code> (suggested by @David Arenburg in the comments).<\/p>\n<pre><code>library(data.table)\nsetDT(df1)[, lapply(.SD, sum), by = .(IsomiR = sub('_.*', '', IsomiR))]  \n<\/code><\/pre>\n<hr>\n<p>Or another option is the formula method in <code>aggregate<\/code> from <code>baseR<\/code> after we <code>transform<\/code> the original dataset  column &#8216;IsomiR` as described above.<\/p>\n<pre><code> aggregate(.~IsomiR, transform(df1, IsomiR= sub('_.*', '', IsomiR)), sum)\n<\/code><\/pre>\n<h3>data<\/h3>\n<pre><code>df1 &lt;- structure(list(IsomiR = c(\"hsa-let-7a-3p_ATACAATCTACTGTCTTTCCT\", \n\"hsa-let-7a-3p_ATATACAATCTACTGTCTTT\", \n\"hsa-let-7a-3p_ATATACAATCTACTGTCTTTC\", \n\"hsa-let-7b-3p_ATATACAATCTACTGTCTTTCC\",\n\"hsa-let-7b-3p_ATATACAATCTACTGTCTTTCT\", \n\"hsa-let-7b-3p_CCATACAATCTACTGTCTTTCT\", \"hsa-let-7b-3p_CTATACAATCTACTGTCTT\", \n\"hsa-let-7c-3p_CTATACAATCTACTGTCTTT\", \"hsa-let-7c-3p_CTATACAATCTACTGTCTTTC\",    \n\"hsa-let-7c-3p_CTATACAATCTACTGTCTTTCA\"), X185R = c(1L, 1L, 4L, \n 7L, 15L, 4L, 2L, 29L, 85L, 11L), X68G = c(6L, 0L, 5L, 5L, 6L, \n1L, 2L, 7L, 24L, 3L), X60G = c(1L, 1L, 2L, 2L, 14L, 1L, 1L, 26L, \n73L, 7L), X134G = c(2L, 1L, 12L, 6L, 49L, 0L, 2L, 21L, 109L, \n8L), X124R = c(2L, 4L, 4L, 3L, 32L, 0L, 3L, 19L, 59L, 3L)),\n.Names = c(\"IsomiR\", \n \"X185R\", \"X68G\", \"X60G\", \"X134G\", \"X124R\"), class = \"data.frame\", \nrow.names = c(NA, -10L))\n<\/code><\/pre>\n<\/p><\/div>\n<div class=\"mt24\"><\/div>\n<\/div>\n<p>            <span class=\"d-none\" itemprop=\"commentCount\">4<\/span> <\/p><\/div>\n<\/div>\n<p>[ad_2]<\/p>\n<p>solved sum lines with similar substring [closed] <\/p>\n","protected":false},"excerpt":{"rendered":"<p>[ad_1] We could match the substring starting from _ to the end of the string (.*$) in &#8216;IsomiR&#8217; column and replace with &#8221; using sub. We use that as the grouping variable. If we are doing this with dplyr, the summarise_each can be used for summing multiple columns. library(dplyr) df1 %&gt;% group_by(IsomiR= sub(&#8216;_.*$&#8217;, &#8221;, IsomiR)) &#8230; <a title=\"[Solved] sum lines with similar substring [closed]\" class=\"read-more\" href=\"https:\/\/jassweb.com\/solved\/solved-sum-lines-with-similar-substring-closed\/\" aria-label=\"More on [Solved] sum lines with similar substring [closed]\">Read more<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[320],"tags":[442,321],"class_list":["post-19443","post","type-post","status-publish","format-standard","hentry","category-solved","tag-perl","tag-r"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>[Solved] sum lines with similar substring [closed] - JassWeb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/jassweb.com\/solved\/solved-sum-lines-with-similar-substring-closed\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"[Solved] sum lines with similar substring [closed] - JassWeb\" \/>\n<meta property=\"og:description\" content=\"[ad_1] We could match the substring starting from _ to the end of the string (.*$) in &#8216;IsomiR&#8217; column and replace with &#039;&#039; using sub. We use that as the grouping variable. If we are doing this with dplyr, the summarise_each can be used for summing multiple columns. library(dplyr) df1 %&gt;% group_by(IsomiR= sub(&#039;_.*$&#039;, &#039;&#039;, IsomiR)) ... 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We use that as the grouping variable. If we are doing this with dplyr, the summarise_each can be used for summing multiple columns. library(dplyr) df1 %&gt;% group_by(IsomiR= sub('_.*$', '', IsomiR)) ... 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