07-reporting.Rmd

# Reporting results


Once we have performed an enrichment analysis, how should we communicate the results? As with everything, it depends on what you need to convey. Some examples are below.

## In text

If you just need to emphasise that the differential expression relates to a condition of interest, you don't need much:

> Genes differentially expressed after SH-SY5Y cell differentiation were enriched for the GO term “regulation of neurogenesis” (adjusted p-value < 0.01).

In the methods section:

> Enrichment was calculated for differentially expressed genes using the g:GOSt enrichment tool [(Raudvere et al, 2019)](https://academic.oup.com/nar/article/47/W1/W191/5486750) using a background of tested genes.


## As a table

For a more complete view, a table of the significant or top _n_ terms can be useful. e.g., in a supplementary figure. 

The top 10 enriched GO terms for the differentially expressed genes are shown below:

| GO:BP Term                               | Term ID    | Adjusted p-value | Term Size | Num DE Genes      |
|------------------------------------------|------------|-----------------:|----------:|------------------:|
| system process                           | GO:0003008 | 2.90E-04         | 1243      | 45                |
| nervous system development               | GO:0007399 | 4.19E-04         | 1985      | 60                |
| regulation of cell development           | GO:0060284 | 1.98E-03         | 795       | 33                |
| central nervous system development       | GO:0007417 | 2.67E-03         | 805       | 33                |
| regulation of neurogenesis               | GO:0050767 | 5.59E-03         | 707       | 30                |
| regulation of nervous system development | GO:0051960 | 5.78E-03         | 790       | 32                |
| regulation of cell differentiation       | GO:0045595 | 6.03E-03         | 1471      | 47                |
| multicellular organismal process         | GO:0032501 | 2.04E-02         | 5300      | 111               |
| system development                       | GO:0048731 | 2.88E-02         | 3668      | 85                |
| neurogenesis                             | GO:0022008 | 4.36E-02         | 1375      | 43                |



## As a figure

Plots of –log(p-value) are a popular option for figures. By taking the negative logarithm of the p-value, larger bars indicate greater significance.

For instance, the following figure is taken from the [(Pezzini et al. 2017)](https://link.springer.com/article/10.1007%2Fs10571-016-0403-y) paper. 
Note that this figure shows two specific categories from the IPA (Ingenuity Pathway Analysis) database using the IPA tool (not covered here), so the terms differ.

<!-- ![](https://monashbioinformaticsplatform.github.io/enrichment_analysis_workshop/img/NegLogPvalPlot_Pezzini2017.png) -->
```{r, out.width="90%", fig.align='center'}
# knitr::include_graphics("https://monashbioinformaticsplatform.github.io/enrichment_analysis_workshop/img/NegLogPvalPlot_Pezzini2017.png")
knitr::include_graphics("images/NegLogPvalPlot_Pezzini2017.png")
```

You can also enhance such plots by including the number of genes and other attributes. For an example, see the "bubble" chart produced by the R package `pathfindR`: https://www.biostars.org/p/322415/

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There are also tools like ClueGO (a Cytoscape plugin) that build enriched terms into a network : http://apps.cytoscape.org/apps/cluego