README.md

In RRHO2/RRHO2: improved RRHO package

RRHO2

Implementation of improved RRHO2, for which all regions in RRHO plots are meaningful.

Install This Package from github

First you need R devtools package installed.

• In R console

library(devtools)
install_github("RRHO2/RRHO2", build_opts = c("--no-resave-data", "--no-manual"))

Citation

• Cahill, K. M., Huo, Z., Tseng, G. C., Logan, R. W., & Seney, M. L. (2018). Improved identification of concordant and discordant gene expression signatures using an updated rank-rank hypergeometric overlap approach. Scientific reports, 8(1), 1-11.

• Plaisier, S. B., Taschereau, R., Wong, J. A., & Graeber, T. G. (2010). Rank–rank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures. Nucleic acids research, 38(17), e169-e169.

Full tutorial

• http://htmlpreview.github.io/?https://github.com/RRHO2/RRHO2/blob/master/vignettes/RRHO2.html

Short tutorial for circadian pattern detection

• Start the package

library(RRHO2)

• Input data format

  • The input gene list should have 2 columns, 1st column is the gene symbol, 2nd column is the input score.
  • The score should be calculated as -log10(pvalue) * sign(effectSize)
  • NA is not allowed
  • Gene symbols of the two gene lists should be identical, but don't have to be in the same order

• Simulate data

set.seed(15213)
nGenes <- 2000
nDE <- 200
Genes <- paste0("Genes",1:nGenes)

## For up-regulated genes, the input score should be calculated using-log10(pvalue) * 1;
## For down-regulated genes, the input score should be calculated using-log10(pvalue) * (-1);

list1_pvalue_1_200 <- runif(nDE,0,0.05) ## up-regulated genes
list1_pvalue_201_400 <- runif(nDE,0,0.05) ## down-regulated genes
list1_pvalue_401_2000 <- runif(nGenes - 2 * nDE,0,1) ## non-changed genes
list1_DDE <- c(-log10(list1_pvalue_1_200), 
    -log10(list1_pvalue_201_400) * (-1), 
    -log10(list1_pvalue_401_2000) * sample(c(1,-1), length(list1_pvalue_401_2000), replace = TRUE))

gene_list1 <- data.frame(Genes=Genes,DDE = list1_DDE, stringsAsFactors = FALSE)

list2_pvalue_1_200 <- runif(nDE,0,0.05)
list2_pvalue_201_400 <- runif(nDE,0,0.05) 
list2_pvalue_401_2000 <- runif(nGenes - 2 * nDE,0,1)
list2_DDE <- c(-log10(list2_pvalue_1_200), -log10(list2_pvalue_201_400) * (-1), 
    -log10(list2_pvalue_401_2000) * sample(c(1,-1), length(list2_pvalue_401_2000), replace = TRUE))

gene_list2 <- data.frame(Genes=Genes,DDE = list2_DDE, stringsAsFactors = FALSE)

• Create the RRHO2 object

RRHO_obj <-  RRHO2_initialize(gene_list1, gene_list2, labels = c("list1", "list2"), log10.ind=TRUE)

• Visualize the heatmap

RRHO2_heatmap(RRHO_obj)

• Visualize the Venn Diagram

RRHO2_vennDiagram(RRHO_obj, type="dd")

RRHO2/RRHO2 documentation built on March 22, 2022, 12:04 p.m.