@@ -1,3 +1,3 @@

-# TDbasedUFEadv 0.99.8

+# TDbasedUFEadv 0.99.9

 * Addressing many comments from reviewers. 

@@ -3,7 +3,7 @@

 #' @param matrix1 the first input matrix

 #' @param matrix2 the second input matrix

 #'

-#' @return A tensor generated from the first and second matricies 

+#' @return A tensor generated from the first and second matrices 

 #' @export

 #'

 #' @examples

@@ -51,14 +51,14 @@ package is similar to [DESeq2](https://doi.org/doi:10.18129/B9.bioc.DESeq2) or [

 identify differentially expressed genes. In contrast to those supervised methods,

 the present method is unsupervised one, which provides users what kind of 

 profiles are observed over samples, and users are advised to select one of

-fivarite features by which features are selected. In addition to this, the

+favorite features by which features are selected. In addition to this, the

 present method is suitable to small number of samples associated with large 

 number of features. Since this situation is very common in genomics, the 

 present method is supposed to be suitable to be applied to genomics, although

 it does not look liked the methods very specific to genomics science. 

-Actually, we have published the number of papers using the metods inplemented 

-in the present package. I hope that one can make uss of this package for his/her

-own reseraches. 

+Actually, we have published the number of papers using the methods implemented 

+in the present package. I hope that one can make use of this package for his/her

+own researches. 

 # Integrated analysis of two omics data sets

@@ -116,12 +116,12 @@ mode (see below), here we assume that you have already finished the selection.

 input_all <- selectSingularValueVectorLarge(HOSVD,cond,input_all=c(2,9)) #Batch mode

 ```

-In the case you prefer to select by yourself  you can execute intearctive mode.

+In the case you prefer to select by yourself  you can execute interactive mode.

 ```

 input_all <- selectSingularValueVectorLarge(HOSVD,cond)

 ```

 When you can see ``Next'', ``Prev'', and ``Select'' radio buttons by which you 

-can performs selection as well as histogram and standard deviation optimiztion

+can performs selection as well as histogram and standard deviation optimization

 by which you can verify the success of selection interactively.

@@ -273,7 +273,7 @@ above, since  vignettes does not allow interactive mode.

 ```

 index_all <- selectFeatureTransRect(HOSVD,cond,de=c(0.01,0.01))

 ```

-and try to select ireratively. Selected features can be shown in the below. 

+and try to select iteratively. Selected features can be shown in the below. 

 ```{r}

 head(tableFeaturesSquare(Z,index_all,1))