In hyginn/BCB420.2019.ESA: Exploratory Systems Analysis Tools

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
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# knitr knits in a new session with an empty global workspace after setting its
# working directory to ./vignettes. To make your package functions available in
# the vignette, you have to load the library. The following two lines should
# accomplish this without manual intervention:
pkgName <- trimws(gsub("^Package:", "", readLines("../DESCRIPTION")[1]))
library(pkgName, character.only = TRUE)

 

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About this Vignette

This is a Vignette about PathwayEnrichment() function of BCB420.2019.ESA package and explain the output visualization of the PathwayEnrichment

The PathwayEnrichment function load the reactome and HGNC gene reference data from the data using helper function, EnrichmentHelper(). The reactome database provides the pathways that each gene can involve. The PathwayEnrichment funcation calculates the number of time a pathway occurs in the given gene set in a system and in the whole reference genes and return a visualization of enrichment. Counting the occuracne can help analysis the enrichment of each pathway that every given gene involve in the system via fisher exact test then adjusted by the bonferroni and BH method. The null hypothesis of the fisher test is the given pathway is not enriched in the given gene set. And the function also apply multiple test correction to adjust the p value. If the adjusted p value is equal to 1, then this pathway is likely to be unenriched.

The more enriched pathways are more likely to involve the system that the given gene set is in.The bar plot shows all the pathways that is enriched, which determined by fisher exact test. The higher the p-value, the higher probabilty that the pathway is involve in this system.

Instruction of using PathwayEnrichment and EnrichmentHelper function

First, users must choose a system and get the genes in this system to analyse.

Presenting the available systems:

source("../R/fetchData.R")
source("../R/SyDButils.R")
names(SyDBgetRootSysIDs(fetchData("SysDB")))

Inserting one system's gene into PathwayEnrichment(). The function uses Bonferroni Correction and Benjamini-Hochberg control

source("../R/fetchData.R")
source("../R/fetchComponents.R")
geneSet <- fetchComponents("PHALY")
reactomeInfo <- fetchData("ReactomeSym")
enrichment <- PathwayEnrichment(geneSet,reactomeInfo)

#apply Multiple test correction
library(ggplot2)
p <- ggplot(data=enrichment[enrichment$pval<enrichment$adjustedPvalBon, c(1,2)], aes(x=pathway, y=pval)) +
      geom_bar(stat="identity", fill="steelblue")+
      theme(legend.direction = "vertical") +
      theme(axis.text.x = element_text(angle = -90)) +
      theme(legend.position = "bottom")
p
#plot for Bonferroni cut off

p <- ggplot(data=enrichment[enrichment$pval<enrichment$adjustedPvalBH, c(1,2)], aes(x=pathway, y=pval)) +
      geom_bar(stat="identity", fill="steelblue")+
      theme(legend.direction = "vertical") +
      theme(axis.text.x = element_text(angle = -90)) +
      theme(legend.position = "bottom")
p

Further reading

• Which 'systems' does this function refer to: Read about the available systems and their notation https://github.com/hyginn/BCB420.2019.ESA.

References

• Calculating P value by using fisher exact test: https://www.pathwaycommons.org/guide/primers/statistics/fishers_exact_test/
• Significance: https://www.pathwaycommons.org/guide/primers/statistics/multiple_testing/

Jüri Reimand, Ruth Isserlin, Veronique Voisin, Mike Kucera, Christian Tannus-Lopes, Asha Rostamianfar, Lina Wadi, Mona Meyer, Jeff Wong, Changjiang Xu, Daniele Merico, Gary D. Bader bioRxiv 232835; doi: https://doi.org/10.1101/232835

hyginn/BCB420.2019.ESA documentation built on May 29, 2019, 1:23 p.m.