text: user9006: I am suddenly running into an error when running the DESeqDataSetFromTximport
  txi.rsem <- tximport(files, type = "rsem", txIn = FALSE, txOut = FALSE)
  dds <- DESeqDataSetFromTximport(txi = txi.rsem,
                                  colData = SampleFile,
                                  design = ~ Compound)`
  
  using counts and average transcript lengths from tximport
  Error in DESeqDataSetFromTximport(txi = txi.rsem, colData = SampleFile,  : 
    all(lengths > 0) is not TRUE 
  
  any suggestions what causes this error?
  
  user9045: I found this same error as of today using this code:
  pad.gene.data <-
    tximport(files = file.list.for.gene.analysis,
             type = "rsem",
             txIn = FALSE,
             txOut = FALSE)
  
  dds.gene.level <-
    DESeqDataSetFromTximport(txi = pad.gene.data,
                             colData = pad.characteristic.data,
                             design = ~ condition)
  
  I had done this same differential gene expression analysis using transcript counts aggregated to the gene level, on a mac about 5 weeks ago, but as of this past week switched to a windows and re-installed R 3.6.3 and whatever the current version of tximport and DESeq2 is.
  I was able to replicate the results I had gotten on the mac 5 weeks ago removing all rows where all gene lengths are greater than 0:
  pad.gene.data$abundance <-
    pad.gene.data$abundance[apply(pad.gene.data$length,
                                  1,
                                  function(row) all(row !=0 )),]
  
  pad.gene.data$counts <-
    pad.gene.data$counts[apply(pad.gene.data$length,
                               1,
                               function(row) all(row !=0 )),]
  
  pad.gene.data$length <-
    pad.gene.data$length[apply(pad.gene.data$length,
                               1,
                               function(row) all(row !=0 )),]
  
  So first removing any gene where there is a length count of 0 from the abundance and counts matrix, then removing the genes from the length matrix so that they are all the same size. It was able to run that way.
  I am definitely skeptical of why I would need to do that as it doesn't seem that it was advertised, if this is a new version, that we need to preprocess the data beforehand. I hope someone who might know more of the code can comment on this.
  
original_text: 9006: <p>I am suddenly running into an error when running the DESeqDataSetFromTximport</p>
  
  <pre><code>txi.rsem &lt;- tximport(files, type = "rsem", txIn = FALSE, txOut = FALSE)
  dds &lt;- DESeqDataSetFromTximport(txi = txi.rsem,
                                  colData = SampleFile,
                                  design = ~ Compound)`
  
  using counts and average transcript lengths from tximport
  Error in DESeqDataSetFromTximport(txi = txi.rsem, colData = SampleFile,  : 
    all(lengths &gt; 0) is not TRUE 
  </code></pre>
  
  <p>any suggestions what causes this error?</p>
   9045: <p>I found this same error as of today using this code:</p>
  <pre><code>pad.gene.data &lt;-
    tximport(files = file.list.for.gene.analysis,
             type = &quot;rsem&quot;,
             txIn = FALSE,
             txOut = FALSE)
  
  dds.gene.level &lt;-
    DESeqDataSetFromTximport(txi = pad.gene.data,
                             colData = pad.characteristic.data,
                             design = ~ condition)
  </code></pre>
  <p>I had done this same differential gene expression analysis using transcript counts aggregated to the gene level, on a mac about 5 weeks ago, but as of this past week switched to a windows and re-installed R 3.6.3 and whatever the current version of tximport and DESeq2 is.</p>
  <p>I was able to replicate the results I had gotten on the mac 5 weeks ago removing all rows where all gene lengths are greater than 0:</p>
  <pre><code>pad.gene.data<span class="math-container">$abundance &lt;-
    pad.gene.data$</span>abundance[apply(pad.gene.data$length,
                                  1,
                                  function(row) all(row !=0 )),]
  
  pad.gene.data<span class="math-container">$counts &lt;-
    pad.gene.data$</span>counts[apply(pad.gene.data$length,
                               1,
                               function(row) all(row !=0 )),]
  
  pad.gene.data<span class="math-container">$length &lt;-
    pad.gene.data$</span>length[apply(pad.gene.data$length,
                               1,
                               function(row) all(row !=0 )),]
  </code></pre>
  <p>So first removing any gene where there is a length count of 0 from the abundance and counts matrix, then removing the genes from the length matrix so that they are all the same size. It was able to run that way.</p>
  <p>I am definitely skeptical of why I would need to do that as it doesn't seem that it was advertised, if this is a new version, that we need to preprocess the data beforehand. I hope someone who might know more of the code can comment on this.</p>
  