glm for multiple variables in R

Question

I wanted to model my snps array. I can do this one by one using the following code.

Data$DX=as.factor(Data$DX)
univariate=glm(relevel(DX, "CON") ~ relevel(rs6693065_D,"AA"), family = binomial, data = Data)
summary(univariate)
exp(cbind(OR = coef(univariate), confint(univariate)))

How can I do this for all other snps using a loop or apply? The snps are rs6693065_D, rs6693065_A and hundreds of them. From the above code only "rs6693065_D" will be replaced by all other snps. Best Regards Zillur

Answer 1

Consider developing a generalized method to handle any snps . Then call it iteratively passing every snps column using lapply or sapply :

# GENERALIZED METHOD
proc_glm <- function(snps) {
   univariate <- glm(relevel(data$DX, "CON") ~ relevel(snps, "AA"), family = binomial)

   return(exp(cbind(OR = coef(univariate), confint(univariate))))
}

# BUILD LIST OF FUNCTION OUTPUT 
glm_list <- lapply(Data[3:426], proc_glm)

Use tryCatch in case of errors like relevel :

# BUILD LIST OF FUNCTION OUTPUT 
glm_list <- lapply(Data[3:426], function(col) 
                   tryCatch(proc_glm(col), error = function(e) e))

---

For building a data frame, adjust method and lapply call followed with a do.call + rbind :

proc_glm <- function(col){
  # BUILD FORMULA BY STRING
  univariate <- glm(as.formula(paste("y ~", col)), family = binomial, data = Data)

  # RETURN DATA FRAME OF COLUMN AND ESTIMATES
  cbind.data.frame(COL = col,
                   exp(cbind(OR = coef(univariate), confint(univariate)))
  )
}

# BUILD LIST OF DFs, PASSING COLUMN NAMES
glm_list <- lapply(names(Data)[3:426], 
                   tryCatch(proc_glm(col), error = function(e) NA))

# APPEND ALL DFs FOR SINGLE MASTER DF
final_df <- do.call(rbind, glm_list)