comparison rmarkdown_deseq2_count_matrix.Rmd @ 2:18e3fc69da76 draft

update tool

1:4a7131658ca6

```{r 'match sample names'}
col_data = col_data[col_names, ]
datatable(col_data)
```

2:18e3fc69da76

```{r 'match sample names'}
col_data = col_data[col_names, ]
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')
```