Sensitivity plot

sensitivity.plot is a function which repeatedly calls the hyprcoloc function to compute a similarity matrix which illustrates how strongly clustered/colocalized pairs of traits are across different input thresholds and priors

Usage

sensitivity.plot(
  effect.est,
  effect.se,
  binary.outcomes = rep(0, dim(effect.est)[2]),
  trait.subset = c(1:dim(effect.est)[2]),
  trait.names = c(1:dim(effect.est)[2]),
  snp.id = c(1:dim(effect.est)[1]),
  ld.matrix = diag(1, dim(effect.est)[1], dim(effect.est)[1]),
  trait.cor = diag(1, dim(effect.est)[2], dim(effect.est)[2]),
  sample.overlap = matrix(rep(1, dim(effect.est)[2]^2), nrow = dim(effect.est)[2]),
  bb.alg = TRUE,
  bb.selection = "regional",
  reg.steps = 1,
  reg.thresh = c(0.6, 0.7, 0.8, 0.9),
  align.thresh = c(0.6, 0.7, 0.8, 0.9),
  prior.1 = 1e-04,
  prior.c = c(0.02, 0.01, 0.005),
  prior.12 = NULL,
  uniform.priors = FALSE,
  ind.traits = TRUE,
  equal.thresholds = FALSE,
  similarity.matrix = FALSE
)

Arguments

effect.est

matrix of snp regression coefficients (i.e. regression beta values) in the genomic region

effect.se

matrix of standard errors associated with the beta values

binary.outcomes

a binary vector of dimension the number of traits: 1 represents a binary trait 0 otherwise

trait.subset

vector of trait names (or number) from the full trait list: used for trageted colocalization analysis in a region

trait.names

vector of trait names corresponding to the columns in the effect.est matrix

snp.id

vector of SNP IDs

ld.matrix

LD matrix

trait.cor

matrix of pairwise correlations between traits

sample.overlap

matrix of pairwise sample overlap between traits

bb.alg

branch and bound algorithm: TRUE, employ BB algorithm; FALSE, do not

bb.selection

branch and bound algorithm type, e.g. regional or alignment selection

reg.steps

regional step paramter

reg.thresh

a vector of regional probability thresholds

align.thresh

a vector of alignment probability thresholds

prior.1

prior probability of a SNP being associated with one trait

prior.c

vector of conditional colocalization priors: where prior.c is the probability of a SNP being associated with an additional trait given that the SNP is associated with at least 1 other trait

prior.12

COLOC prior p12: prior probability of a SNP being associated with any two traits

uniform.priors

uniform priors

ind.traits

are the traits independent or to be treated as independent

equal.thresholds

fix the regional and alignment thresholds to be equal

similarity.matrix

To be viewed as a similarity matrix. Default FALSE.

Author

Christopher Foley chris.neal.foley@gmail.com & James Staley jrstaley95@gmail.com