analyzeGenePairs: Analyze Gene Pairs

Description Usage Arguments Value Examples

View source: R/analyzeGenePairs.R

Description

Comaprison of two genes of interest using correlation values. This can be 2 different genes in the same tissue or sample type or the same gene accross two sample or tissue types. Alternatively, specify 'crossCompareMode' to view compared correrlations across all available tissue types.

Usage

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analyzeGenePairs(genesOfInterest, Sample_Type = c("normal", "normal"),
  Tissue = c("all", "all"), Species = c("hsapiens", "mmusculus"),
  GSEA_Type = c("simple"),
  outputPrefix = "CorrelationAnalyzeR_Output_Paired",
  crossCompareMode = FALSE, runGSEA = TRUE, TERM2GENE = NULL,
  nperm = 2000, sampler = FALSE, topPlots = FALSE,
  returnDataOnly = TRUE, pool = NULL, makePool = FALSE)

Arguments

genesOfInterest

A length-two vector with genes to compare.

Sample_Type

A length-two vector of sample types corresponding to genesOfInterest. Choose "all", "normal", or "cancer". Default: c("normal", "normal")

Tissue

A length-two vector of tissue types corresponding to genesOfInterest. Run getTissueTypes() to see available list. Default: c("all", "all")

Species

Species to obtain gene names for. Either 'hsapiens' or 'mmusculus'. Default: "hsapiens".

GSEA_Type

Which GSEA annotations should be considered? Options listed in correlationAnalyzeR::pathwayCategories – See details of getTERM2GENE for more info.

outputPrefix

Prefix for saved files – the directory name to store output files in. If folder does not exist, it will be created.

crossCompareMode

Use this mode to generate comparisons across all tissue and disease types. If both genes for genesOfInterest are the same – will compare normal vs cancer for that gene in each available tissue. Else, will perform comparison of two different genes in all tissue-disease groups. Will only consider user input for returnDataOnly, outputPrefix, Species, and genesOfInterest.

runGSEA

If TRUE will run GSEA using gene correlation values.

TERM2GENE

Mapping of geneset IDs to gene names. If NULL, it will be generated automatically. Only applicable if GSEA is to be run.

nperm

Number of permutations to run in GSEA. Default is 2000

sampler

If TRUE, will only return 100,000 random genesets. Useful for reducing GSEA computational burden.

topPlots

Logical. If TRUE, myGSEA() will build gsea plots for top correlated genesets.

returnDataOnly

if TRUE will return result list object and will not generate any folders or files.

pool

an object created by pool::dbPool to accessing SQL database. It will be created if not supplied.

makePool

Logical. Should a pool be created if one is not supplied? Default: FALSE.

Value

A named list containing visualizations and correlation data from paired analysis.

Examples

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genesOfInterest <- c("ATM", "SLC7A11")
correlationAnalyzeR::analyzeGenePairs(genesOfInterest = genesOfInterest,
                              Species = "hsapiens",
                              GSEA_Type = "simple", returnDataOnly = TRUE,
                              Sample_Type = c("normal", "normal"),
                              Tissue = c("brain", "brain"))
genesOfInterest <- c("BRCA1", "BRCA1")
correlationAnalyzeR::analyzeGenePairs(genesOfInterest = genesOfInterest,
                              Species = "hsapiens",
                              GSEA_Type = "simple", returnDataOnly = TRUE,
                              Sample_Type = c("normal", "cancer"),
                              Tissue = c("respiratory", "respiratory"))
genesOfInterest <- c("NFKB1", "SOX10")
correlationAnalyzeR::analyzeGenePairs(genesOfInterest = genesOfInterest,
                              Species = "hsapiens", returnDataOnly = TRUE,
                              crossCompareMode = TRUE)

millerh1/correlationAnalyzeR documentation built on Dec. 10, 2019, 1:31 a.m.