Changes between Version 18 and Version 19 of SOPs/rna-seq-diff-expressions

Timestamp:

09/10/14 14:03:47 (10 years ago)

Author:

byuan

Comment:

--

SOPs/rna-seq-diff-expressions

@@ -112 +112 @@
     * Fold change thresholds may be used in addition, if desired, to select genes that are changing an amount that is biologically meaningful.
 
+ * **Remove batch effects**
+    * With [[http://www.bioconductor.org/packages/release/bioc/html/edgeR.html|edgeR]], the treatments can be adjusted for differences between the batch with addictive model formula by design = model.matrix( ~Batch+Treatment). For example, with target.txt like this:
+
+
+   ||= Sample =||= genotype =||= date =|| 
+   ||  KO.1  || KO || old ||
+   ||  KO.2  || KO      || old ||
+   ||  WT.1  || WT      || old ||
+   ||  KO.3  || KO      || new ||
+   ||  KO.4  || KO      || new ||
+   ||  WT.2  || WT      || new ||
+
+
+  Sample R codes for reducing the date effect (old/new) are
+
+ {{{
+   target   <- read.delim("target.txt", header=T)
+   genotype <- factor(target$genotype, levels=c("WT", "KO"))
+   mydate   <- factor(target$date, levels=c("old", "new"))
+   Design   <-model.matrix(~mydate+genotype)
+   colnames(Design)
+# [1] "(Intercept)" "mydatenew"   "genotypeKO" 
+
+   Y2  <- calcNormFactors(Y) # Y is the DGEList
+   Y2  <- estimateGLMCommonDisp(Y2, Design, verbose=TRUE)
+   Y2  <- estimateGLMTrendedDisp(Y2, Design)
+   Y2  <- estimateGLMTagwiseDisp(Y2, Design)
+   Fit <- glmFit(Y2, Design)
+   Lrt <- glmLRT(Fit, coef="genotypeKO") # coef is pointed to the column name in Design
+ }}}
+
+  Lrt$table has the log2FC(Fold change) and P-value.
+   
+  Detail information can be found in [[http://www.bioconductor.org/packages/release/bioc/html/edgeR.html|edgeR]]
+
+
  * **Other**
    * Review articles: