text: user2005: I have a data.frame of 27 000 x 17 and I want to feed it into UpSetR program, but getting the error:
  
  Error in start_col:end_col : argument of length 0
  
  My data.frame looks like that:
  
  And the upSetR code that I am using:
  upset(df, nsets = 4, number.angles = 30, point.size = 3.5, line.size = 2, 
  mainbar.y.label = "Gene Intersections", sets.x.label = "Genes Per Group", 
  text.scale = c(1.3, 1.3, 1, 1, 2, 0.75))
  
  What am I doing wrong here? Any suggestions would be greatly appreciated.
  
  Update
  
  I found here a similar issue: 
  https://plus.google.com/109635504520741246387/posts/Etujrp6sU1Q
  They say that the input should be binary. But then, how can I calculate this binary matrix from the rlog-data? I am not sure...
  
  user6219: I wrote a script to create the binary data frame with my differential expression data. If it is of any help to anyone:
  
  user6363: You need to generate a list of gene ID vectors to feed into upset. In the example below, I am selecting observations (genes) which have an level above the median level. You could also choose only genes above the 3rd quartile, etc. You then need to convert these from a list of character vectors to a presence/absence matrix. UpSetR has a fromList function that does just this.
  In future, be more specific about what you want to achieve and supply example data for people to work with.
  library("UpSetR")
  
  tmp <- mtcars
  
  tmp$car <- rownames(mtcars)
  list <- lapply(colnames(mtcars), function(x) {
    tmp[tmp[[x]] > median(tmp[[x]]), "car"]
  })
  names(list) <- colnames(mtcars)
  
  upset(fromList(list))
  
  
  Created on 2019-10-17 by the reprex package (v0.3.0)
  
original_text: 2005: <p>I have a <code>data.frame</code> of <code>27 000 x 17</code> and I want to feed it into <code>UpSetR</code> program, but getting the error:</p>
  
  <blockquote>
    <p>Error in start_col:end_col : argument of length 0</p>
  </blockquote>
  
  <p>My <code>data.frame</code> looks like that:</p>
  
  <p><a href="https://i.stack.imgur.com/dzQ7h.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/dzQ7h.png" alt="enter image description here"></a></p>
  
  <p>And the <code>upSetR</code> code that I am using:</p>
  
  <pre><code>upset(df, nsets = 4, number.angles = 30, point.size = 3.5, line.size = 2, 
  mainbar.y.label = "Gene Intersections", sets.x.label = "Genes Per Group", 
  text.scale = c(1.3, 1.3, 1, 1, 2, 0.75))
  </code></pre>
  
  <p>What am I doing wrong here? Any suggestions would be greatly appreciated.</p>
  
  <blockquote>
    <p>Update</p>
  </blockquote>
  
  <p>I found here a similar issue: </p>
  
  <p><a href="https://plus.google.com/109635504520741246387/posts/Etujrp6sU1Q" rel="nofollow noreferrer">https://plus.google.com/109635504520741246387/posts/Etujrp6sU1Q</a></p>
  
  <p>They say that the input should be binary. But then, how can I calculate this binary matrix from the <code>rlog</code>-data? I am not sure...</p>
   6219: <p>I wrote a <a href="https://github.com/sdmiller93/Public_Scripts/blob/master/up_down_flat.R" rel="nofollow noreferrer">script</a> to create the binary data frame with my differential expression data. If it is of any help to anyone:</p>
   6363: <p>You need to generate a list of gene ID vectors to feed into <code>upset</code>. In the example below, I am selecting observations (genes) which have an level above the median level. You could also choose only genes above the 3rd quartile, etc. You then need to convert these from a list of character vectors to a presence/absence matrix. UpSetR has a <code>fromList</code> function that does just this.</p>
  
  <p>In future, be more specific about what you want to achieve and supply example data for people to work with.</p>
  
  <pre class="lang-r prettyprint-override"><code>library("UpSetR")
  
  tmp &lt;- mtcars
  
  tmp$car &lt;- rownames(mtcars)
  list &lt;- lapply(colnames(mtcars), function(x) {
    tmp[tmp[[x]] &gt; median(tmp[[x]]), "car"]
  })
  names(list) &lt;- colnames(mtcars)
  
  upset(fromList(list))
  </code></pre>
  
  <p><img src="https://i.imgur.com/7RJcGCG.png" alt=""></p>
  
  <p><sup>Created on 2019-10-17 by the <a href="https://reprex.tidyverse.org" rel="nofollow noreferrer">reprex package</a> (v0.3.0)</sup></p>
  