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Correct rendering of titles #19

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8 changes: 4 additions & 4 deletions vignettes/biobroom_vignette.Rmd
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Expand Up @@ -167,7 +167,7 @@ ggplot(tidy_results, aes(x=estimate, y=log(p.value),
ggtitle("Volcano Plot For Airway Data via DESeq2") + theme_bw()
```

##edgeR objects
## edgeR objects

Here we use the `hammer` dataset included in `biobroom` package. `edgeR` can be used to perform differential
expression analysis as follows:
Expand Down Expand Up @@ -206,7 +206,7 @@ ggplot(tidy(et), aes(x=estimate, y=log(p.value), color=logCPM)) +
theme_bw()
```

##limma objects
## limma objects

To demonstrate how `biobroom` works with `limma` objects, we generate some simulated data to test the tidier for `limma` objects.

Expand Down Expand Up @@ -241,7 +241,7 @@ ggplot(tidy(eb), aes(x=estimate, y=log(p.value), color=statistic)) +
```


##ExpressionSet objects
## ExpressionSet objects

`tidy` can also be run directly on `ExpressionSet` objects, as described in another popular `Bioconductor` package `Biobase.` The
`hammer` dataset we used above (which is included in the `biobroom` package) is an `ExpressionSet` object, so we'll use that to demonstrate.
Expand All @@ -265,7 +265,7 @@ ggplot(tidy(hammer, addPheno=TRUE), aes(x=protocol, y=log(value))) +
geom_boxplot() + ggtitle("Boxplot Showing Effect of Protocol on Expression")
```

##MSnSet Objects
## MSnSet Objects

`tidy` can also be run directly on `MSnSet` objects from `MSnbase`, which as specialised containers for quantitative proteomics data.

Expand Down