fix error

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: DAtest
 Title: Comparing Differential Abundance methods
-Version: 2.7.9
+Version: 2.7.10
 Authors@R: person("Jakob", "Russel", email = "russel2620@gmail.com", role = c("aut", "cre"))
 Description: What the title says.
 Depends: R (>= 3.2.5)

R/DA.llm2.R

@@ -130,19 +130,19 @@ DA.llm2 <- function(data, predictor, paired = NULL, covars = NULL, out.all = NUL
           fit <- lme(as.formula(form), random = ~1|paired, ...), error = function(e) fit <- NULL)
       }
     }
-    return(apply(count_table,1,lmr))
+    return(apply(count.rel,1,lmr))
   } else {
     if(out.all){
       if(is.null(paired)){
-        res <- as.data.frame(do.call(rbind,apply(count_table,1,lmr)))
+        res <- as.data.frame(do.call(rbind,apply(count.rel,1,lmr)))
         colnames(res)[1:5] <- c("Df","Sum Sq","Mean Sq","F value","pval")
       } else {
-        res <- as.data.frame(do.call(rbind,apply(count_table,1,lmr)))
+        res <- as.data.frame(do.call(rbind,apply(count.rel,1,lmr)))
         colnames(res)[1:4] <- c("numDF","denDF","F-value","pval")
       }
       res <- as.data.frame(lapply(res, unlist))
     } else {
-      res <- as.data.frame(t(as.data.frame(apply(count_table,1,lmr))))
+      res <- as.data.frame(t(as.data.frame(apply(count.rel,1,lmr))))
       colnames(res)[ncol(res)] <- "pval"
       res$log2FC <- log2((res[,coeff.ref]+res[,coeff]) / res[,coeff.ref])
       res[res[,coeff.ref] < 0 & !is.na(res[,coeff.ref]), "log2FC"] <- NA

R/DA.ltt.R

@@ -55,7 +55,7 @@ DA.ltt <- function(data, predictor, paired = NULL, relative = TRUE, p.adj = "fdr
         tryCatch(t.test(x ~ predictor, paired = TRUE, ...), error = function(e){NA}) 
       }
     }
-    return(apply(count.rel,1,tt))
+    return(apply(count_table,1,tt))
   } else {
     res <- data.frame(pval = apply(count_table,1,tt))
     res$pval.adj <- p.adjust(res$pval, method = p.adj)

R/DA.per.R

@@ -62,15 +62,15 @@ DA.per <- function(data, predictor, paired = NULL, relative = TRUE, p.adj = "fdr
     }
   }
 
-  iterations <- nrow(count_table)
+  iterations <- nrow(count.rel)
   p <- numeric(iterations)
   FC <- numeric(iterations)
   coverage <- numeric(iterations)
 
   # For each feature
   for(i in 1:iterations){
 
-    count_row      <- as.numeric(count_table[i,])
+    count_row      <- as.numeric(count.rel[i,])
 
     real_case    <- count_row[predictor==1]
     real_control <- count_row[predictor==0]

R/zzz.R

@@ -1,5 +1,5 @@
 
 .onLoad <- function(libname, pkgname){
-  message("DAtest version 2.7.9")
+  message("DAtest version 2.7.10")
 }