Gene List Prioritization using WikiPathways Pathway Enrichment

Required File

From the previous step, you should have a tsv from the pathway enrichment analysis against the WikiPathways database. For this example, we will call this file
wiki_protein_enrichment.tsv

Extract pathway IDs from tsv and generate gene list

Place the tsv into your working directory (otherwise specify the path) and extract the pathway labels into a data frame (second column will contain the pathway IDs)

file = "wiki_protein_enrichment.tsv"
wiki.pathways = load.WebGestalt(file,'Wiki')

Now we can use the list of pathways to generate a gene list.

Wikigene.ids = get.genes.wiki(wiki.pathways)

Create prioritized gene list from transcriptomic data

First load the gene data, which in this example will be

Cattaneo_array.csv

This data (and other example files) can be downloaded from here in addition to using our R function:

download.example.data()

The load.gene.data function requires a string pointing to the location of the data file and an integer ≥2 that indicates which column the actual data starts. In this example, it is the fifth column. This will generate two data frames, the second is formatted and transposed version of the original data with a $label column added.

file = "Cattaneo_array.csv"
Cattaneo.rna = load.gene.data(file,5)
Wikiprioritized.data = list.filter(Cattaneo.rna$transposed.data,Wikigene.ids)

This data frame will have the transposed data prioritized data from the original transcriptomic data frame. In this example if we wanted to perform statistics on this data we could use the Wikiprioritized.data$label to assign class labels.

In the next step we will apply an independent filter to this data.