Downstreamer

Downstreamer can be used to to perform key gene prioritization using GWAS summary statistics. We do this using 57 tissue specific co-expression networks derived from the Recount3 data.

Content

1️⃣ Getting started
2️⃣ Running PascalX to obtain gene p-values
3️⃣ Tissue enrichment
4️⃣ Key gene enrichment
5️⃣ Code availability

1. Getting started

Download tool and reference data here:

2. Running PascalX to obtain gene p-values

Downstreamer needs gene level p-values for the analysis. PascalX can be used to convert the variant level summary statistics of GWAS to gene level summary statistics.

The instruction to do so are listed here: PascalX for Downstreamer

Note. in principle Downstreamer can also use gene p-values from another source. This is however not recommend as you would then also need to create a new null distribution for the gene p-values.

3. Tissue enrichment

First we use Downstreamer to determine which tissue express the genes implicated by the GWAS using a tissue enrichment analysis. By doing this we make sure that the key genes predictions are driven by relevant co-expression instead of cell tissue specific expression.

For this first run: runDownstreamerTissueEnrichment.sh followed by the R code in: selectSignficantTissues.R

This will prepare a parameter specifying which tissue specific networks Downstreamer should use in the next step.

4. Key gene enrichment

We are now ready to run the actual key gene prioritization. This done by: runDownstreamerKeygenePrediction.sh

The resulting key gene prioritization per tissue are found in: _keygene_enrichtments.xlsx

5. Code availability

https://github.com/molgenis/systemsgenetics/tree/master/Downstreamer