title: Performing rowwise t.test on a dataframe with unequal replicates for different observations
body: <p>Say for example, I have a dataframe that has eleven columns (example screenshot attached). The first column lists all the genes and the next ten columns are measurements for control <code>(C1-C5)</code> and treated <code>(T1-T5)</code> samples. The measurements are not paired.<br> 
  I want to perform rowwise t.test and add a column with p-value for each gene as a last column of the dataframe. However, as you can see in my data, I don't have all measurements for all replicates (both in control and treatment conditions) for every gene because of the way the experiment was performed. So I have several NA values in many rows.<br>
  How do I perform rowwise t.test in this dataframe without it failing because of the NA values? Thanks! </p>
  
  <p><a href="https://i.stack.imgur.com/nMOaf.png" rel="nofollow noreferrer">example data</a></p>