text: user14978: What are some possible reasons why some trends observed in Microarray expression levels is not observed in RNA-seq. Example the difference between 2 cell types for a gene of interest show major differences when microarray is used with one cell type clearly having higher expression but rna-seq for the same cell types shows equal expression levels for the gene of interest?
  What are possible explanations for the discrepancy between such results ? Shouldn't they have relatively identical trends otherwise gene expression in one of them is unreliable?
  
  user14180: That is a good question. I have never done any Microarray experiments or data analysis myself. But I am very familiar with RNA-seq library workflows and data analysis. Library prep methods for RNA-seq involves many steps including use of several enzymes, which introduce certain level of bias. For example, reverse transcriptase used for making cDNA may copy certain mRNA sequences better than others. Other steps that involve enzymes: second strand synthesis, end-repair, ligation, and PCR amplification. Non-enzymatic steps could also introduce biases. I imagine Microarray and probe designs have also significant biases. There could be additional reasons I have not mentioned above, such as improper data analysis. If global gene expression levels are significantly different, I would suspect that it could be experimental reasons e.g. bad lab practices, unreliable reagents etc. I hope this helps.
  
original_text: 14978: <p>What are some possible reasons why some trends observed in Microarray expression levels is not observed in RNA-seq. Example the difference between 2 cell types for a gene of interest show major differences when microarray is used with one cell type clearly having higher expression but rna-seq for the same cell types shows equal expression levels for the gene of interest?</p>
  <p>What are possible explanations for the discrepancy between such results ? Shouldn't they have relatively identical trends otherwise gene expression in one of them is unreliable?</p>
   14180: <p>That is a good question. I have never done any Microarray experiments or data analysis myself. But I am very familiar with RNA-seq library workflows and data analysis. Library prep methods for RNA-seq involves many steps including use of several enzymes, which introduce certain level of bias. For example, reverse transcriptase used for making cDNA may copy certain mRNA sequences better than others. Other steps that involve enzymes: second strand synthesis, end-repair, ligation, and PCR amplification. Non-enzymatic steps could also introduce biases. I imagine Microarray and probe designs have also significant biases. There could be additional reasons I have not mentioned above, such as improper data analysis. If global gene expression levels are significantly different, I would suspect that it could be experimental reasons e.g. bad lab practices, unreliable reagents etc. I hope this helps.</p>
  