hakyim

qqR2 <- function(corvec,nn,pad_neg_with_0 = FALSE,...)
{
## nn is the sample size, number of individuals used to compute correlation.
## needs correlation vector as input.
## nullcorvec generates a random sample from correlation distributions, under the null hypothesis of 0 correlation using Fisher's approximation.
  if(pad_neg_with_0) corvec[corvec < 0 | is.na(corvec) ]=0
  mm <- length(corvec)
  nullcorvec = tanh(rnorm(mm)/sqrt(nn-3)) ## null correlation vector
  qqplot(nullcorvec^2,corvec^2,...); abline(0,1); grid()
}

hakyim

## May 7, 2012
## Hae Kyung Im
## haky@uchicago.edu
##


## Please cite:
## Eric R Gamazon, R. Stephanie Huang, Eileen Dolan, Nancy Cox, and Hae Kyung Im, (2012)
## Integrative Genomics: Quantifying significance of phenotype-genotype
## relationships from multiple sources of high-throughput data

hakyim

## pvalue vs uniform

qqunif = 
  function(p,BH=T,CI=T,mlog10_p_thres=30,...)
  {
    ## thresholded by default at 1e-30
    p=na.omit(p)
    nn = length(p)
    xx =  -log10((1:nn)/(nn+1))