Y叔的书 笔记记录

Y叔的书 - 笔记

chapter 3 - universal enrichment analysis

input data

for gene set enrichment analysis - a ranked list of genes

​ note : no duplicated gene ID allowed

example

# 使用‘DOSE’包中的示例数据
data(geneList, package="DOSE")
head(geneList)

#设定fold change 大于2倍的为差异表达基因
gene <- names(geneList)[abs(geneList) > 2]
head(gene)

wikipathways analysis

​ a continuously updated pathway database by a community of researchers

monthly releases of gmt files

Download the appropriate gmt file & generate TERM2GENE & TERM2NAME to use enricher & GSEA functions

library(magrittr)
suppressPackageStartupMessages(library(clusterProfiler))

data(geneList, package="DOSE")
str(geneList)
gene <- names(geneList)[abs(geneList) > 2]
head(gene)

wpgmtfile <- system.file("extdata/wikipathways-20180810-gmt-Homo_sapiens.gmt", package="clusterProfiler")
wp2gene <- read.gmt(wpgmtfile)
wp2gene <- wp2gene %>% tidyr::separate(ont, c("name","version","wpid","org"), "%")
wpid2gene <- wp2gene %>% dplyr::select(wpid, gene) #TERM2GENE
wpid2name <- wp2gene %>% dplyr::select(wpid, name) #TERM2NAME
# 真得学好tidyr / dplyr这几个包

ewp <- enricher(gene, TERM2GENE = wpid2gene, TERM2NAME = wpid2name) 
head(ewp)

also, you can install the rWikiPathways package to manually download gmt file

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("rWikiPathways")
# use downloadPathwayArchive function to download the latest gmt files

cell marker

cell_markers <- vroom::vroom('http://bio-bigdata.hrbmu.edu.cn/CellMarker/download/Human_cell_markers.txt') %>%
  tidyr::unite("cellMarker", tissueType, cancerType, cellName, sep=", ") %>% 
  dplyr::select(cellMarker, geneID) %>%
  dplyr::mutate(geneID = strsplit(geneID, ', '))
cell_markers

y <- enricher(gene, TERM2GENE=cell_markers, minGSSize=1)
DT::datatable(as.data.frame(y))

MSigDb analysis

​ Molecular Signatures Database - 8 major collections

download gmt files from Broad Institute

H: hallmark gene sets

C1: positional gene sets

C2: curated gene sets

C3: motif gene sets

C4: computational gene sets

C5: GO gene sets

C6: oncogenic signatures

C7: immunologic signatures

package msigdbr - recommend by uncle Y

library(msigdbr)
msigdbr_show_species()

# retrieve all human gene sets
m_df <- msigdbr(species = "Homo sapiens")
head(m_df, 2) %>% as.data.frame

# or specific collection
m_t2g <- msigdbr(species = "Homo sapiens", category = "C6") %>% 
  dplyr::select(gs_name, entrez_gene)
head(m_t2g)

question:

​ as mentioned by uncle Y:

​ "using C3 to test whether the genes are up/down-regulated by sharing specific motif"

​ background knowledge - C3