09-MeSH.Rmd

# MeSH Enrichment Analysis {#chapter9}


`meshes` supports enrichment analysis (over-representation analysis and gene set
enrichment analysis) of gene list or whole expression profile using MeSH
annotation. Data source from `gendoo`, `gene2pubmed` and `RBBH` are all
supported. User can selecte interesting category to test. All 16
categories are supported. The analysis supports >70 species listed in [MeSHDb BiocView](https://bioconductor.org/packages/release/BiocViews.html#___MeSHDb).

For algorithm details, please refer to the vignettes of `r Biocpkg("DOSE")`[@yu_dose_2015] package.

```{r}
library(meshes)
data(geneList, package="DOSE")
de <- names(geneList)[1:100]
x <- enrichMeSH(de, MeSHDb = "MeSH.Hsa.eg.db", database='gendoo', category = 'C')
head(x)
```


In the over-representation analysis, we use data source from `gendoo` and `C` (Diseases) category.

In the following example, we use data source from `gene2pubmed` and test category `G` (Phenomena and Processes) using GSEA.

```{r}
y <- gseMeSH(geneList, MeSHDb = "MeSH.Hsa.eg.db", database = 'gene2pubmed', category = "G")
head(y)
```

User can use visualization methods implemented in `r Biocpkg("enrichplot")` (i.e.`barplot`, `dotplot`, `cnetplot`, `emapplot` and `gseaplot`) to visualize these enrichment results. With these visualization methods, it's much easier to interpret enriched results.


```{r}
dotplot(x)
gseaplot(y, y[1,1], title=y[1,2])
```