text: user7354: I have gene expression data from RNAseq, specifically: log2(x+1) transformed RSEM normalized counts.
  How can I convert these data from multiple samples to determine fold change in gene expression?
  
  user-1: You should use a proper statistical framework for RNA-seq dfferential analysis (which includes FC calculation). Standard tools for this are (among others) edgeR or DESeq2. You could use tximport to import RSEM outputs into R and then use its output for e.g. DESeq2. The linked manual provides example code for this. Please read the manuals of edgeR or DESeq2 towards the respective downstream analysis. Both are extensive and compreshensive.
  
original_text: 7354: <p>I have gene expression data from RNAseq, specifically: log2(x+1) transformed RSEM normalized counts.</p>
  
  <p>How can I convert these data from multiple samples to determine fold change in gene expression?</p>
   -1: <p>You should use a proper statistical framework for RNA-seq dfferential analysis (which includes FC calculation). Standard tools for this are (among others) <code>edgeR</code> or <code>DESeq2</code>. You could use <a href="https://bioconductor.org/packages/release/bioc/vignettes/tximport/inst/doc/tximport.html#rsem" rel="nofollow noreferrer">tximport</a> to import RSEM outputs into R and then use its output for e.g. <code>DESeq2</code>. The linked manual provides example code for this. Please read the manuals of <code>edgeR</code> or <code>DESeq2</code> towards the respective downstream analysis. Both are extensive and compreshensive.</p>
  