Changes between Version 47 and Version 48 of SOPs/rna-seq-diff-expressions

Timestamp:

06/15/17 10:16:50 (8 years ago)

Author:

gbell

Comment:

--

SOPs/rna-seq-diff-expressions

@@ -79 +79 @@
   * **Quantification by FPKM (Fragments Per Kilobase of transcript per Million mapped reads)**
 
-    * '''Method 1''': Use [http://cole-trapnell-lab.github.io/cufflinks/manual/ cufflinks] 
+    * Method 1: Use [http://cole-trapnell-lab.github.io/cufflinks/manual/ cufflinks] 
       * This is the traditional method.
 
@@ -100 +100 @@
 }}}
     
-    * '''Method 2''': Use the fpkm() function from DESeq2.  This method requires raw counts and any measure of gene length (such as mean or median length of transcripts of gene) that one needs to produce independently (or create a GRanges data structure).  It can produce (raw) FPKMs [using fpkm(... robust = FALSE)] and normalized FPKMs [using fpkm(... robust = TRUE)].
-
-    * '''Method 3''': Using Cuffquant to get '''normalized''' FPKMs, as described with [http://cole-trapnell-lab.github.io/monocle-release/getting-started/ monocle] and [http://cole-trapnell-lab.github.io/cufflinks/cuffnorm/#running-cuffnorm Cuffnorm]. The default normalization for Cuffnorm is the same than the normalization performed by DESeq.
-
-    * '''Method 4''': Use featureCounts
+    * Method 2: Use the fpkm() function from DESeq2.  This method requires raw counts and any measure of gene length (such as mean or median length of transcripts of gene) that one needs to produce independently (or create a GRanges data structure).  It can produce (raw) FPKMs [using fpkm(... robust = FALSE)] and normalized FPKMs [using fpkm(... robust = TRUE)].
+
+    * Method 3: Using Cuffquant to get '''normalized''' FPKMs, as described with [http://cole-trapnell-lab.github.io/monocle-release/getting-started/ monocle] and [http://cole-trapnell-lab.github.io/cufflinks/cuffnorm/#running-cuffnorm Cuffnorm]. The default normalization for Cuffnorm is the same than the normalization performed by DESeq.
+
+    * Method 4: Use featureCounts
       * Gene-level FPKM values are calculated from gene-level counts, corrected for library size and "gene length", as defined by the length of the non-redundant overlap of all exons of all transcripts of that gene.  Typically this method overestimates gene length since the length of a gene is by definition at least as long as every transcript defining the gene.