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Gene and gene-set analysis

Table of Contents

MAGMA Introduction

MAGMA is one of the most commonly used tools for gene-based and gene-set analysis.

Overview of MAGMA

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Gene-level analysis in MAGMA uses two models:

1.Multiple linear principal components regression

MAGMA employs a multiple linear principal components regression, and F test to obtain P values for genes. The multiple linear principal components regression:

\[ Y = \alpha_{0,g} + X_g \alpha_g + W \beta_g + \epsilon_g \]
  • \(X_g\) : principal component matrix
  • \(\alpha_g\) : genetic effects
  • \(W\) : covariate matrix
  • \(\beta_g\) : effects of covariates

\(X_g\) is obtained by first projecting the variant matrix of a gene onto its PC, and removing PCs with small eigenvalues.

Note

The linear principal components regression model requires raw genotype data.

2.SNP-wise models

SNP-wise Mean: perform tests on mean SNP association

Note

SNP-wise models use summary statistics and reference LD panel

Gene-set analysis

Quote

Competitive gene-set analysis tests whether the genes in a gene-set are more strongly associated with the phenotype of interest than other genes.

P values for each gene were converted to Z scores to perform gene-set level analysis.

\[ Z = \beta_{0,S} + S_S \beta_S + \epsilon \]
  • \(S_S\) : indicator (if the gene is in a specified gene set)
  • \(\beta_S\) : difference in effects between genes in the specified set and genes outside the set.

Install MAGMA

Download MAGMA for your operating system from the following URL:

MAGMA: https://ctg.cncr.nl/software/magma

For example: 

cd ~/tools
mkdir MAGMA
cd MAGMA
wget https://ctg.cncr.nl/software/MAGMA/prog/magma_v1.10.zip
unzip magma_v1.10.zip
Add magma to your environment path.

Test if it is successfully installed. 

$ magma --version
MAGMA version: v1.10 (linux)

Download reference files

We need the following reference files:

  • gene location files
  • LD reference panel
  • Gene-set files

The gene location files and LD reference panel can be downloaded from magma website.

-> https://ctg.cncr.nl/software/magma

The third one can be downloaded from MsigDB.

-> https://www.gsea-msigdb.org/gsea/msigdb/

Format input files

zcat ../08_LDSC/BBJ_HDLC.txt.gz | awk 'NR>1 && $2==3 {print $1,$2,$3}' > HDLC_chr3.magma.input.snp.chr.pos.txt
zcat ../08_LDSC/BBJ_HDLC.txt.gz | awk 'NR>1 && $2==3 {print $1,10^(-$11)}' >  HDLC_chr3.magma.input.p.txt

Annotate SNPs

snploc=./HDLC_chr3.magma.input.snp.chr.pos.txt
ncbi37=~/tools/magma/NCBI37/NCBI37.3.gene.loc
magma --annotate \
      --snp-loc ${snploc} \
      --gene-loc ${ncbi37} \
      --out HDLC_chr3

Tip

Usually, to capture the variants in the regulatory regions, we will add windows upstream and downstream of the genes with --annotate window.

For example, --annotate window=35,10 set a 35 kilobase pair(kb) upstream and 10kb downstream window.

Gene-based analysis

ref=~/tools/magma/g1000_eas/g1000_eas
magma \
    --bfile $ref \
    --pval ./HDLC_chr3.magma.input.p.txt N=70657 \
    --gene-annot HDLC_chr3.genes.annot \
    --out HDLC_chr3

Gene-set level analysis

geneset=/home/he/tools/magma/MSigDB/msigdb_v2022.1.Hs_files_to_download_locally/msigdb_v2022.1.Hs_GMTs/msigdb.v2022.1.Hs.entrez.gmt
magma \
    --gene-results HDLC_chr3.genes.raw \
    --set-annot ${geneset} \
    --out HDLC_chr3

Reference

  • de Leeuw, Christiaan A., et al. "MAGMA: generalized gene-set analysis of GWAS data." PLoS computational biology 11.4 (2015): e1004219.