twosigma (version 1.0.2)

adhoc.twosigma: adhoc.twosigma: Perform the ad hoc method described in TWO-SIGMA paper

Description

adhoc.twosigma: Perform the ad hoc method described in TWO-SIGMA paper

Usage

adhoc.twosigma(
  count,
  mean_covar,
  zi_covar,
  id,
  weights = rep(1, length(count))
)

Arguments

count

Vector of non-negative integer read counts.

mean_covar

Covariates for the (conditional) mean model. Must be a matrix (without an intercept column) or = 1 to indicate an intercept only model.

zi_covar

Covariates for the zero-inflation model. Must be a matrix (without an intercept column), = 1 to indicate an intercept only model, or = 0 to indicate no zero-inflation model desired.

id

Vector of individual-level ID's. Used as predictor in ANOVA model.

weights

weights, as in glm. Defaults to 1 for all observations and no scaling or centering of weights is performed. Passed into zeroinfl function.

Value

P-value from the ANOVA F test.

Examples

# NOT RUN {
# Set Parameters to Simulate Some Data

nind<-10;ncellsper<-rep(50,nind)
sigma.a<-.5;sigma.b<-.5;phi<-.1
alpha<-c(1,0,-.5,-2);beta<-c(2,0,-.1,.6)
beta2<-c(2,1,-.1,.6)
id.levels<-1:nind;nind<-length(id.levels)
id<-rep(id.levels,times=ncellsper)
sim.seed<-1234

# Simulate individual level covariates

t2d_sim<-rep(rbinom(nind,1,p=.4),times=ncellsper)
cdr_sim<-rbeta(sum(ncellsper),3,6)
age_sim<-rep(sample(c(20:60),size=nind,replace = TRUE),times=ncellsper)

# Construct design matrices

Z<-cbind(scale(t2d_sim),scale(age_sim),scale(cdr_sim))
colnames(Z)<-c("t2d_sim","age_sim","cdr_sim")
X<-cbind(scale(t2d_sim),scale(age_sim),scale(cdr_sim))
colnames(X)<-c("t2d_sim","age_sim","cdr_sim")

# Simulate Data

sim_dat<-matrix(nrow=2,ncol=sum(ncellsper))
for(i in 1:nrow(sim_dat)){
   sim_dat[i,]<-simulate_zero_inflated_nb_random_effect_data(ncellsper,X,Z,alpha,beta2
   ,phi,sigma.a,sigma.b,id.levels=NULL)$Y
}
rownames(sim_dat)<-paste("Gene",1:2)

# Run adhoc.twosigma

adhoc.twosigma(sim_dat[1,],mean_covar = X,zi_covar=Z,id = id)
# }