text: user1377: I recently read the paper “A novel long non-coding RNA linc-ZNF469-3 promotes lung metastasis through miR-574-5p-ZEB1 axis in triple negative breast cancer”. In this I see Table1 showing correlation of Linc-ZNF469-3 with different features in TNBC and non-TNBC patients. p-values are calculated based on Pearson's Chi-sq test.
  
  For non-TNBC patients: I calculated the p-value with the Chi-sq test just to have a look if everything is right.
  Recurrence:
  data <- data.frame(x= c(40,62), y=c(56,65))
  data
  chisq.test(data, correct = F)
  
      Pearson's Chi-squared test
  
  data:  data
  X-squared = 1.1269, df = 1, p-value = 0.2884
  
  Brain:
  data <- data.frame(x= c(6,99), y=c(6,119))
  data
  chisq.test(data, correct = F)
  
      Pearson's Chi-squared test
  
  data:  data
  X-squared = 0.096461, df = 1, p-value = 0.7561
  
  You can see that the Recurrence p-value doesn't match with what I see in the table. Others, like Brain, Bone, Liver, Lung match with the p-values I calculated.
  And for TNBC patients, not a single p-value matches with my calculations. I don't even get Lung and Bone as having significant p-values with my calculations.
  I did it for Lung as shown here:
  data <- data.frame(x= c(25,143), y=c(9,35))
  data
  chisq.test(data, correct = F)
  
      Pearson's Chi-squared test
  
  data:  data
  X-squared = 0.8044, df = 1, p-value = 0.3698
  
  But in the paper they mentioned:
  
  We found that high linc-ZNF469-3 expression was significantly correlated to lung metastasis in TNBC patients (Table 1).
  
  Can anyone tell me what could be the wrong here? Is it my calculation wrong? or in the paper?
  
  user48: Your calculations seem right, perhaps there was an error on their side. 
  I also looked at the number of samples reported, but they use the same amount of samples in each case. Because they are testing whether Linc-ZNF469-3 is different in several tissues, they should have used a multiple test correction for the p-value (although reporting the original values is usually also ok). 
  To answer your question in the comments. You can't correlate a categorical variable with a continuous  variable. Or they did another test or they are not explaining clearly what they did.
  
original_text: 1377: <p>I recently read the paper <a href="https://www.nature.com/articles/s41388-018-0293-1" rel="nofollow noreferrer">“A novel long non-coding RNA <em>linc-ZNF469-3</em> promotes lung metastasis through <em>miR-574-5p-ZEB1</em> axis in triple negative breast cancer”</a>. In this I see Table1 showing correlation of Linc-ZNF469-3 with different features in TNBC and non-TNBC patients. p-values are calculated based on Pearson's Chi-sq test.</p>
  
  <p><a href="https://i.stack.imgur.com/puQ8D.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/puQ8D.png" alt="enter image description here"></a></p>
  
  <p>For non-TNBC patients: I calculated the p-value with the Chi-sq test just to have a look if everything is right.</p>
  
  <p>Recurrence:</p>
  
  <pre><code>data &lt;- data.frame(x= c(40,62), y=c(56,65))
  data
  chisq.test(data, correct = F)
  
      Pearson's Chi-squared test
  
  data:  data
  X-squared = 1.1269, df = 1, p-value = 0.2884
  </code></pre>
  
  <p>Brain:</p>
  
  <pre><code>data &lt;- data.frame(x= c(6,99), y=c(6,119))
  data
  chisq.test(data, correct = F)
  
      Pearson's Chi-squared test
  
  data:  data
  X-squared = 0.096461, df = 1, p-value = 0.7561
  </code></pre>
  
  <p>You can see that the Recurrence p-value doesn't match with what I see in the table. Others, like Brain, Bone, Liver, Lung match with the p-values I calculated.</p>
  
  <p>And for TNBC patients, not a single p-value matches with my calculations. I don't even get Lung and Bone as having significant p-values with my calculations.</p>
  
  <p>I did it for Lung as shown here:</p>
  
  <pre><code>data &lt;- data.frame(x= c(25,143), y=c(9,35))
  data
  chisq.test(data, correct = F)
  
      Pearson's Chi-squared test
  
  data:  data
  X-squared = 0.8044, df = 1, p-value = 0.3698
  </code></pre>
  
  <p>But in the paper they mentioned:</p>
  
  <blockquote>
    <p>We found that high linc-ZNF469-3 expression was significantly correlated to lung metastasis in TNBC patients (Table 1).</p>
  </blockquote>
  
  <p>Can anyone tell me what could be the wrong here? Is it my calculation wrong? or in the paper?</p>
   48: <p>Your calculations seem right, perhaps there was an error on their side. </p>
  
  <p>I also looked at the number of samples reported, but they use the same amount of samples in each case. Because they are testing whether Linc-ZNF469-3 is different in several tissues, they should have used a multiple test correction for the p-value (although reporting the original values is usually also ok). </p>
  
  <p>To answer your question in the comments. You can't correlate a categorical variable with a continuous  variable. Or they did another test or they are not explaining clearly what they did.</p>
  