Enrichment-class: An S4 class Enrichment
In mcanouil/snpEnrichment: SNPs Enrichment Analysis With Sampling

Description Slots Objects from the Class Examples

This class is defined to summarize the enrichment analysis on each chromosomes and the whole genome.

Signal: A three columns data.frame: "SNP", "PVALUE" and "IN" (e.g., GWAS). "IN" is computed during the reading step and gives informations about which SNPs are kept for the enrichment analysis.
Loss: A four columns data.frame: "Rows", "Unique", "Intersect.Ref.Signal" and "CIS". This slot gives information on data losses.
Call: Each parameters used for the reading or resampling step are stored in this slot.
eSNP: Contain a EnrichSNP object for a list of SNPs (eSNP).
xSNP: Contain a EnrichSNP object for a extended list of SNPs (xSNP).
Chromosomes: A list of 22 Chromosome objects.

Enrichment is defined to build an object of class Enrichment in order to compute an enrichment analysis. Enrichment is the object containing the results for all Chromosome object and for the whole genome.

When an Enrichment object is created, it contains a list of SNPs (e.g., eSNPs). All the others slots are "empty". After reSample is ran on an Enrichment object, the slots: Table, EnrichmentRatio, Z, PValue and Resampling are filled.

Note that if reSample is executed on an Enrichment every new resampling is added to the original ones, pre-existing statistics are erased and computed again with the new resampling set.

data(toyEnrichment)
toyEnrich <- enrichment()
show(toyEnrich)

toyEnrich["Loss"] <- toyEnrichment["Loss"]
toyEnrich["Loss"]

toyEnrich <- enrichment(Loss = toyEnrichment["Loss"], eSNP = toyEnrichment["eSNP"])
toyEnrich <- enrichment(Loss = toyEnrichment["Loss"])

if (interactive()) {
  reSample(
    object = toyEnrichment,
    nSample = 10,
    empiricPvalue = TRUE,
    MAFpool = c(0.05, 0.10, 0.2, 0.3, 0.4, 0.5),
    mc.cores = 1,
    onlyGenome = TRUE
  )
  print(toyEnrichment)

  excludeFile <- c(
    "rs7897180", "rs4725479", "rs315404", "rs17390391", "rs1650670",
    "rs6783390", "rs1642009", "rs4756586", "rs11995037", "rs4977345",
    "rs13136448", "rs4233536", "rs11151079", "rs2299657", "rs4833930",
    "rs1384", "rs7168184", "rs6909895", "rs7972667", "rs2293229",
    "rs918216", "rs6040608", "rs2817715", "rs13233541", "rs4486743",
    "rs2127806", "rs10912854", "rs1869052", "rs9853549", "rs448658",
    "rs2451583", "rs17483288", "rs10962314", "rs9612059", "rs1384182",
    "rs8049208", "rs12215176", "rs2980996", "rs1736976", "rs8089268",
    "rs10832329", "rs12446540", "rs7676237", "rs869922", "rs16823426",
    "rs1374393", "rs13268781", "rs11134505", "rs7325241", "rs7520109"
  )

  toyEnrichment_exclude <- excludeSNP(toyEnrichment, excludeFile, mc.cores = 1)
  print(toyEnrichment_exclude)
}