How to Download MSigDB Database Glycolysis-Related Genes

We received a question from a bioinformatics beginner marathon student, what should we do!!! Of course, we should pamper her! The question is as follows:

First, I searched for relevant information

Using keywords to search in WeChat: MSigDB database glycolysis-related genes. I found an article published in October 2022 in the journal Frontiers in Endocrinology: Identification of risk model based on glycolysis-related genes in the metastasis of osteosarcoma. This article used a collection of glycolysis-related pathway genes:

We obtained 5 glycolysis-related pathway gene sets from MSigDB, namely:

• BIOCARTA GLYCOLYSIS PATHWAY
• GO GLYCOLYTIC PROCESS,
• HALLMARK GLYCOLYSIS,
• KEGG GLYCOLYSIS GLUCONEOGENESIS,
• REACTOME GLYCOLYSIS.

I feel there should be more than 5 gene sets!

I also saw another article published in August 2023 in the journal Cancer Cell Int titled Glycolysis-related biomarker TCIRG1 participates in regulation of renal cell carcinoma progression and tumor immune microenvironment by affecting aerobic glycolysis and AKT/mTOR signaling pathway, which also provided specific instructions on how to search for glycolysis-related genes from the MSigDB database:

Of course, we can directly download the supplementary table table2 from this article, but the MSigDB database underwent a major update in 2024, as mentioned in the article: What are the reasons for the failure to obtain gene sets from the msigdbr database?, we still recommend checking the latest data!

The article found 21 pathways:

Let’s see how to implement it with code

We will use the keyword glycolysis to search the MSigDB database: https://www.gsea-msigdb.org/gsea/msigdb/index.jsp.

First, download the entire library, the file is less than 30M:

library(clusterProfiler)
library(org.Hs.eg.db)
library(GSEABase)

## === All pathways
geneset <- read.gmt("msigdb.v2024.1.Hs.symbols.gmt")
length(unique(geneset$term))
head(as.data.frame(table(geneset$term)))

There are a total of 34837 gene sets:

Only found 13 pathways, which is fewer than the above article. Looking at the pathways above, some gene sets do not contain the keyword glycolysis:

# Search for glycolysis-related gene sets: glycolysis
geneset_select <- geneset[grep(pattern ="glycolysis", geneset$term,ignore.case = T),]
str(geneset_select)
as.data.frame(table(as.character(geneset_select$term)))

Web Version Search and Download

The above code can only retrieve gene sets with the keyword in their names; there may be other gene sets that do not have this keyword but have glycolysis-related functions. See the method below to obtain the file: genesets.v2024.1.Hs.gmt, which has 22 gene sets, one more than the article above:

Read it in R to see:

### Web Download
geneset <- read.gmt("genesets.v2024.1.Hs.gmt")
length(unique(geneset$term))
as.data.frame(table(geneset$term))

This way, we have obtained all the glycolysis-related genes, and we can happily use them later!

If you have similar questions, you can check the links below:

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