# HG changeset patch
# User mingchen0919
# Date 1514670121 18000
# Node ID 18e3fc69da76c28af0bfa87cf50e9ed4aab03770
# Parent 4a7131658ca681b5e0bd272618b7acdf196c4381
update tool
diff -r 4a7131658ca6 -r 18e3fc69da76 rmarkdown_deseq2_count_matrix.Rmd
--- a/rmarkdown_deseq2_count_matrix.Rmd Sat Dec 30 12:35:31 2017 -0500
+++ b/rmarkdown_deseq2_count_matrix.Rmd Sat Dec 30 16:42:01 2017 -0500
@@ -54,3 +54,54 @@
datatable(col_data)
```
+# DESeqDataSet
+
+```{r 'DeseqDataSet'}
+dds = DESeqDataSetFromMatrix(countData = count_data,
+ colData = col_data,
+ design = formula(opt$design_formula))
+dds
+```
+
+Pre-filter low count genes
+
+```{r 'pre-filtering'}
+keep = rowSums(counts(dds)) >= 10
+dds = dds[keep, ]
+dds
+```
+
+# Differential expression analysis
+
+```{r 'differential expression analysis'}
+dds = DESeq(dds)
+# res = results(dds, contrast = c(opt$contrast_condition, opt$treatment, opt$control))
+res = results(dds)
+resultsNames(dds)
+if(nrow(res) > 500) {
+ cat('The result table has more than 500 rows. Only 500 rows are randomly selected to dispaly.')
+ datatable(as.data.frame(res)[sample(1:nrow(res), 500), ])
+} else {
+ datatable(as.data.frame(res))
+}
+```
+
+
+
+```{r 'write results into csv'}
+#Write results into a CSV file.
+write.csv(res, 'differential_genes.csv')
+```
+
+# MAplot
+
+```{r}
+plotMA(res)
+```
+
+
+```{r 'save R objects'}
+# Save R objects to a file
+save(dds, opt, file = 'deseq2.RData')
+```
+
diff -r 4a7131658ca6 -r 18e3fc69da76 rmarkdown_deseq2_count_matrix.xml
--- a/rmarkdown_deseq2_count_matrix.xml Sat Dec 30 12:35:31 2017 -0500
+++ b/rmarkdown_deseq2_count_matrix.xml Sat Dec 30 16:42:01 2017 -0500
@@ -56,6 +56,8 @@
+