diff --git a/DESCRIPTION b/DESCRIPTION
index b9130e4..8e80ad5 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: mnem
 Type: Package
 Title: Mixture Nested Effects Models
-Version: 0.99.7
+Version: 0.99.8
 Author: Martin Pirkl
 Maintainer: Martin Pirkl <martin.pirkl@bsse.ethz.ch>
 Description: Mixture Nested Effects Models (mnem) is an extension of Nested Effects Models and allows for the analysis of single cell perturbation data provided by methods like Perturb-Seq (Dixit et al., 2016) or Crop-Seq (Datlinger et al., 2017). In those experiments each of many cells is perturbed by a knock-down of a specific gene, i.e. several cells are perturbed by a knock-down of gene A, several by a knock-down of gene B, ... and so forth. The observed read-out has to be multi-trait and in the case of the Perturb-/Crop-Seq gene are expression profiles for each cell. mnem uses a mixture model to simultaneously cluster the cell population into k clusters and and infer k networks causally linking the perturbed genes for each cluster. The mixture components are inferred via an expectation maximization algorithm.
diff --git a/R/mnems.r b/R/mnems.r
index d095088..f0aed02 100644
--- a/R/mnems.r
+++ b/R/mnems.r
@@ -798,7 +798,7 @@ plot.bootmnem <- function(x, reduce = TRUE, ...) {
         adj[bidi] <- (adj2+t(adj2))[bidi]
         diag(adj) <- 0
         dnf <- adj2dnf(apply(adj, c(1,2), ceiling))
-        dnf <- dnf[-(1:nrow(adj))]
+        dnf <- dnf[-seq_len(nrow(adj))]
         freq <- as.vector(t(adj))
         freq <- freq[which(freq != 0)]
         dnfs <- c(dnfs, dnf)