deleted file mode 100755

@@ -1,57 +0,0 @@

-\name{plotDataFrame}

-\alias{plotDataFrame}

-\title{

-Quickly visualize a data frame

-}

-\description{

-Quickly visualize a data frame

-}

-\usage{

-plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE,

-    show_column_names = TRUE, group = NULL, group_names = names(group),

-    main_heatmap = NULL, km = 1, split = NULL, cluster_rows = TRUE,

-    cluster_columns = TRUE, row_order = NULL, ...)

-}

-\arguments{

-

-  \item{df}{a data frame.}

-  \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are treated as under same measurement and should be grouped.}

-  \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded, because it doesn't make any sense to visualize a character vector or matrix that contains huge number of unique elements through a heatmap.}

-  \item{show_row_names}{whether show row names after the last heatmap if there are row names.}

-  \item{show_column_names}{whether show column names for all heatmaps.}

-  \item{group}{a list of index that defines the groupping.}

-  \item{group_names}{names for each group.}

-  \item{main_heatmap}{which group is the main heatmap?}

-  \item{km}{a value larger than 1 means applying k-means clustering on rows for the main heatmap.}

-  \item{split}{one or multiple variables that split the rows.}

-  \item{cluster_rows}{whether perform clustering on rows of the main heatmap.}

-  \item{cluster_columns}{whether perform clustering on columns for all heatmaps.}

-  \item{row_order}{order of rows, remember to turn off \code{cluster_rows}}

-  \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}}

-

-}

-\details{

-The data frame contains heterogeneous information. The \code{\link{plotDataFrame}} function provides a simple and quick way to

-visualize information that are stored in a data frame.

-

-There are only a few settings in this function, so the heamtap generated by this functioin

-may look ugly (in most of the time). However, users can customize the style of the heatmaps by manually

-constructing a \code{\link{HeatmapList}} object.

-}

-\value{

-A \code{\link{HeatmapList}} object.

-}

-\author{

-Zuguang Gu <z.gu@dkfz.de>

-}

-\examples{

-df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

-                large = runif(10)*100,

-                t1 = sample(letters[1:3], 10, replace = TRUE),

-                matrix(runif(60), nrow = 10, dimnames = list(LETTERS[1:10], LETTERS[1:6])),

-                t2 = sample(LETTERS[1:3], 10, replace = TRUE))

-plotDataFrame(df)

-plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"),

-    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")

-

-}

@@ -10,13 +10,13 @@ Quickly visualize a data frame

 plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE,

     show_column_names = TRUE, group = NULL, group_names = names(group),

     main_heatmap = NULL, km = 1, split = NULL, cluster_rows = TRUE,

-    cluster_columns = TRUE, ...)

+    cluster_columns = TRUE, row_order = NULL, ...)

 }

 \arguments{

   \item{df}{a data frame.}

-  \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in thecurrent column and previous numeric column is larger than this value, the two columnsare treated as under same measurement and should be grouped.}

-  \item{nlevel}{If the number of levels of a character column is larger than this value, the column willbe excluded, because it doesn't make any sense to visualize a character vector or matrixthat contains huge number of unique elements through a heatmap.}

+  \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are treated as under same measurement and should be grouped.}

+  \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded, because it doesn't make any sense to visualize a character vector or matrix that contains huge number of unique elements through a heatmap.}

   \item{show_row_names}{whether show row names after the last heatmap if there are row names.}

   \item{show_column_names}{whether show column names for all heatmaps.}

   \item{group}{a list of index that defines the groupping.}

@@ -26,6 +26,7 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE,

   \item{split}{one or multiple variables that split the rows.}

   \item{cluster_rows}{whether perform clustering on rows of the main heatmap.}

   \item{cluster_columns}{whether perform clustering on columns for all heatmaps.}

+  \item{row_order}{order of rows, remember to turn off \code{cluster_rows}}

   \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}}

 }

old mode 100644

new mode 100755

@@ -33,12 +33,12 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE,

 The data frame contains heterogeneous information. The \code{\link{plotDataFrame}} function provides a simple and quick way to

 visualize information that are stored in a data frame.

-There are only a few advanced settings in this function, so the heamtap generated by this functioin

+There are only a few settings in this function, so the heamtap generated by this functioin

 may look ugly (in most of the time). However, users can customize the style of the heatmaps by manually

 constructing a \code{\link{HeatmapList}} object.

 }

 \value{

-a \code{\link{HeatmapList}} object.

+A \code{\link{HeatmapList}} object.

 }

 \author{

 Zuguang Gu <z.gu@dkfz.de>

@@ -32,6 +32,7 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE,

 \details{

 The data frame contains heterogeneous information. The \code{\link{plotDataFrame}} function provides a simple and quick way to

 visualize information that are stored in a data frame.

+

 There are only a few advanced settings in this function, so the heamtap generated by this functioin

 may look ugly (in most of the time). However, users can customize the style of the heatmaps by manually

 constructing a \code{\link{HeatmapList}} object.

@@ -10,7 +10,8 @@ Quickly visualize a data frame

 plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE,

     show_column_names = TRUE, group = NULL, group_names = names(group),

     main_heatmap = NULL, km = 1, split = NULL, cluster_rows = TRUE,

-    cluster_columns = TRUE, ...)}

+    cluster_columns = TRUE, ...)

+}

 \arguments{

   \item{df}{a data frame.}

@@ -26,6 +27,7 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE,

   \item{cluster_rows}{whether perform clustering on rows of the main heatmap.}

   \item{cluster_columns}{whether perform clustering on columns for all heatmaps.}

   \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}}

+

 }

 \details{

 The data frame contains heterogeneous information. The \code{\link{plotDataFrame}} function provides a simple and quick way to

@@ -49,4 +51,5 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett

 plotDataFrame(df)

 plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"),

     main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")

+

 }

@@ -2,11 +2,9 @@

 \alias{plotDataFrame}

 \title{

 Quickly visualize a data frame

-

 }

 \description{

 Quickly visualize a data frame

-

 }

 \usage{

 plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE,

@@ -32,33 +30,17 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE,

 \details{

 The data frame contains heterogeneous information. The \code{\link{plotDataFrame}} function provides a simple and quick way to

 visualize information that are stored in a data frame.

-

 There are only a few advanced settings in this function, so the heamtap generated by this functioin

 may look ugly (in most of the time). However, users can customize the style of the heatmaps by manually

 constructing a \code{\link{HeatmapList}} object.

-

 }

 \value{

 a \code{\link{HeatmapList}} object.

-

 }

 \author{

 Zuguang Gu <z.gu@dkfz.de>

-

 }

 \examples{

-

-

-

-

-

-

-

-

-

-

-

-

 df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

                 large = runif(10)*100,

                 t1 = sample(letters[1:3], 10, replace = TRUE),

@@ -66,4 +48,5 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett

                 t2 = sample(LETTERS[1:3], 10, replace = TRUE))

 plotDataFrame(df)

 plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"),

-    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")}

+    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")

+}

@@ -54,6 +54,11 @@ Zuguang Gu <z.gu@dkfz.de>

+

+

+

+

+

 df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

                 large = runif(10)*100,

                 t1 = sample(letters[1:3], 10, replace = TRUE),

@@ -53,6 +53,7 @@ Zuguang Gu <z.gu@dkfz.de>

+

 df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

                 large = runif(10)*100,

                 t1 = sample(letters[1:3], 10, replace = TRUE),

@@ -49,6 +49,10 @@ Zuguang Gu <z.gu@dkfz.de>

 \examples{

+

+

+

+

 df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

                 large = runif(10)*100,

                 t1 = sample(letters[1:3], 10, replace = TRUE),

@@ -47,6 +47,8 @@ Zuguang Gu <z.gu@dkfz.de>

 }

 \examples{

+

+

 df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

                 large = runif(10)*100,

                 t1 = sample(letters[1:3], 10, replace = TRUE),

@@ -1,44 +1,45 @@

 \name{plotDataFrame}

 \alias{plotDataFrame}

 \title{

-Visualize a data frame

+Quickly visualize a data frame

 }

 \description{

-Visualize a data frame

+Quickly visualize a data frame

 }

 \usage{

-plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_column_names = TRUE,

-    group = NULL, group_names = names(group), main_heatmap = NULL, km = 1, split = NULL,

-    cluster_rows = TRUE, cluster_columns = TRUE, ...)}

+plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE,

+    show_column_names = TRUE, group = NULL, group_names = names(group),

+    main_heatmap = NULL, km = 1, split = NULL, cluster_rows = TRUE,

+    cluster_columns = TRUE, ...)}

 \arguments{

-  \item{df}{a data frame}

-  \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in thecurrent column and previous numeric column is larger than this value, the two columnsare thought under same measurement and should be grouped.}

-  \item{nlevel}{If the number of levels of a character column is larger than this value, the column willbe excluded.}

+  \item{df}{a data frame.}

+  \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in thecurrent column and previous numeric column is larger than this value, the two columnsare treated as under same measurement and should be grouped.}

+  \item{nlevel}{If the number of levels of a character column is larger than this value, the column willbe excluded, because it doesn't make any sense to visualize a character vector or matrixthat contains huge number of unique elements through a heatmap.}

   \item{show_row_names}{whether show row names after the last heatmap if there are row names.}

-  \item{show_column_names}{whether show column names for all heatmaps}

-  \item{group}{a list of index that defines the groupping}

-  \item{group_names}{names for each group}

-  \item{main_heatmap}{which group is the main heatmap}

-  \item{km}{apply k-means clustering on rows for the main heatmap}

-  \item{split}{set a splitting variable on rows for the main heatmap}

-  \item{cluster_rows}{whether perform clustering on rows of the first heatmap}

-  \item{cluster_columns}{whether perform clustering on columns for all heatmaps}

+  \item{show_column_names}{whether show column names for all heatmaps.}

+  \item{group}{a list of index that defines the groupping.}

+  \item{group_names}{names for each group.}

+  \item{main_heatmap}{which group is the main heatmap?}

+  \item{km}{a value larger than 1 means applying k-means clustering on rows for the main heatmap.}

+  \item{split}{one or multiple variables that split the rows.}

+  \item{cluster_rows}{whether perform clustering on rows of the main heatmap.}

+  \item{cluster_columns}{whether perform clustering on columns for all heatmaps.}

   \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}}

 }

 \details{

-The data frame contains information from different aspects and different measurements are applied

-on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to

+The data frame contains heterogeneous information. The \code{\link{plotDataFrame}} function provides a simple and quick way to

 visualize information that are stored in a data frame.

-There are not many advanced settings in this function. Users can customize the style of the heatmaps

-by constructing a \code{\link{HeatmapList}} object.

+There are only a few advanced settings in this function, so the heamtap generated by this functioin

+may look ugly (in most of the time). However, users can customize the style of the heatmaps by manually

+constructing a \code{\link{HeatmapList}} object.

 }

 \value{

-a \code{\link{HeatmapList}} object

+a \code{\link{HeatmapList}} object.

 }

 \author{

@@ -46,7 +47,6 @@ Zuguang Gu <z.gu@dkfz.de>

 }

 \examples{

-

 df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

                 large = runif(10)*100,

                 t1 = sample(letters[1:3], 10, replace = TRUE),

@@ -46,6 +46,7 @@ Zuguang Gu <z.gu@dkfz.de>

 }

 \examples{

+

 df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

                 large = runif(10)*100,

                 t1 = sample(letters[1:3], 10, replace = TRUE),

@@ -46,8 +46,6 @@ Zuguang Gu <z.gu@dkfz.de>

 }

 \examples{

-

-

 df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

                 large = runif(10)*100,

                 t1 = sample(letters[1:3], 10, replace = TRUE),

@@ -46,6 +46,8 @@ Zuguang Gu <z.gu@dkfz.de>

 }

 \examples{

+

+

 df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

                 large = runif(10)*100,

                 t1 = sample(letters[1:3], 10, replace = TRUE),

@@ -46,8 +46,6 @@ Zuguang Gu <z.gu@dkfz.de>

 }

 \examples{

-

-

 df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

                 large = runif(10)*100,

                 t1 = sample(letters[1:3], 10, replace = TRUE),

@@ -55,6 +53,4 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett

                 t2 = sample(LETTERS[1:3], 10, replace = TRUE))

 plotDataFrame(df)

 plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"),

-    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")

-

-}

+    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")}

@@ -47,6 +47,7 @@ Zuguang Gu <z.gu@dkfz.de>

 }

 \examples{

+

 df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

                 large = runif(10)*100,

                 t1 = sample(letters[1:3], 10, replace = TRUE),

@@ -46,6 +46,7 @@ Zuguang Gu <z.gu@dkfz.de>

 }

 \examples{

+

 df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

                 large = runif(10)*100,

                 t1 = sample(letters[1:3], 10, replace = TRUE),

@@ -53,4 +54,6 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett

                 t2 = sample(LETTERS[1:3], 10, replace = TRUE))

 plotDataFrame(df)

 plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"),

-    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")}

+    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")

+

+}

@@ -1,25 +1,22 @@

 \name{plotDataFrame}

 \alias{plotDataFrame}

 \title{

-Visualize a data frame  

-

+Visualize a data frame

 }

 \description{

-Visualize a data frame  

-

+Visualize a data frame

 }

 \usage{

 plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_column_names = TRUE,

     group = NULL, group_names = names(group), main_heatmap = NULL, km = 1, split = NULL,

-    cluster_rows = TRUE, cluster_columns = TRUE, ...)

-}

+    cluster_rows = TRUE, cluster_columns = TRUE, ...)}

 \arguments{

   \item{df}{a data frame}

-  \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are thought under same measurement and should be grouped.}

-  \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded.}

+  \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in thecurrent column and previous numeric column is larger than this value, the two columnsare thought under same measurement and should be grouped.}

+  \item{nlevel}{If the number of levels of a character column is larger than this value, the column willbe excluded.}

   \item{show_row_names}{whether show row names after the last heatmap if there are row names.}

   \item{show_column_names}{whether show column names for all heatmaps}

   \item{group}{a list of index that defines the groupping}

@@ -30,23 +27,22 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_colum

   \item{cluster_rows}{whether perform clustering on rows of the first heatmap}

   \item{cluster_columns}{whether perform clustering on columns for all heatmaps}

   \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}}

-

 }

 \details{

-The data frame contains information from different aspects and different measurements are applied on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to visualize information that are stored in a data frame.  

-

-There are not many advanced settings in this function. Users can customize the style of the heatmaps by constructing a \code{\link{HeatmapList}} object.  

+The data frame contains information from different aspects and different measurements are applied

+on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to

+visualize information that are stored in a data frame.

+There are not many advanced settings in this function. Users can customize the style of the heatmaps

+by constructing a \code{\link{HeatmapList}} object.

 }

 \value{

-a \code{\link{HeatmapList}} object  

-

+a \code{\link{HeatmapList}} object

 }

 \author{

-Zuguang Gu <z.gu@dkfz.de>  

-

+Zuguang Gu <z.gu@dkfz.de>

 }

 \examples{

@@ -57,5 +53,4 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett

                 t2 = sample(LETTERS[1:3], 10, replace = TRUE))

 plotDataFrame(df)

 plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"),

-    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")

-}

+    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")}

@@ -1,22 +1,25 @@

 \name{plotDataFrame}

 \alias{plotDataFrame}

 \title{

-Visualize a data frame

+Visualize a data frame  

+

 }

 \description{

-Visualize a data frame

+Visualize a data frame  

+

 }

 \usage{

 plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_column_names = TRUE,

     group = NULL, group_names = names(group), main_heatmap = NULL, km = 1, split = NULL,

-    cluster_rows = TRUE, cluster_columns = TRUE, ...)}

+    cluster_rows = TRUE, cluster_columns = TRUE, ...)

+}

 \arguments{

   \item{df}{a data frame}

-  \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in thecurrent column and previous numeric column is larger than this value, the two columnsare thought under same measurement and should be grouped.}

-  \item{nlevel}{If the number of levels of a character column is larger than this value, the column willbe excluded.}

+  \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are thought under same measurement and should be grouped.}

+  \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded.}

   \item{show_row_names}{whether show row names after the last heatmap if there are row names.}

   \item{show_column_names}{whether show column names for all heatmaps}

   \item{group}{a list of index that defines the groupping}

@@ -27,22 +30,23 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_colum

   \item{cluster_rows}{whether perform clustering on rows of the first heatmap}

   \item{cluster_columns}{whether perform clustering on columns for all heatmaps}

   \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}}

+

 }

 \details{

-The data frame contains information from different aspects and different measurements are applied

-on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to

-visualize information that are stored in a data frame.

+The data frame contains information from different aspects and different measurements are applied on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to visualize information that are stored in a data frame.  

+

+There are not many advanced settings in this function. Users can customize the style of the heatmaps by constructing a \code{\link{HeatmapList}} object.  

-There are not many advanced settings in this function. Users can customize the style of the heatmaps

-by constructing a \code{\link{HeatmapList}} object.

 }

 \value{

-a \code{\link{HeatmapList}} object

+a \code{\link{HeatmapList}} object  

+

 }

 \author{

-Zuguang Gu <z.gu@dkfz.de>

+Zuguang Gu <z.gu@dkfz.de>  

+

 }

 \examples{

@@ -53,4 +57,5 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett

                 t2 = sample(LETTERS[1:3], 10, replace = TRUE))

 plotDataFrame(df)

 plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"),

-    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")}

+    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")

+}

@@ -1,25 +1,22 @@

 \name{plotDataFrame}

 \alias{plotDataFrame}

 \title{

-Visualize a data frame  

-

+Visualize a data frame

 }

 \description{

-Visualize a data frame  

-

+Visualize a data frame

 }

 \usage{

 plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_column_names = TRUE,

     group = NULL, group_names = names(group), main_heatmap = NULL, km = 1, split = NULL,

-    cluster_rows = TRUE, cluster_columns = TRUE, ...)

-}

+    cluster_rows = TRUE, cluster_columns = TRUE, ...)}

 \arguments{

   \item{df}{a data frame}

-  \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are thought under same measurement and should be grouped.}

-  \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded.}

+  \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in thecurrent column and previous numeric column is larger than this value, the two columnsare thought under same measurement and should be grouped.}

+  \item{nlevel}{If the number of levels of a character column is larger than this value, the column willbe excluded.}

   \item{show_row_names}{whether show row names after the last heatmap if there are row names.}

   \item{show_column_names}{whether show column names for all heatmaps}

   \item{group}{a list of index that defines the groupping}

@@ -30,23 +27,22 @@ plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_colum

   \item{cluster_rows}{whether perform clustering on rows of the first heatmap}

   \item{cluster_columns}{whether perform clustering on columns for all heatmaps}

   \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}}

-

 }

 \details{

-The data frame contains information from different aspects and different measurements are applied on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to visualize information that are stored in a data frame.  

-

-There are not many advanced settings in this function. Users can customize the style of the heatmaps by constructing a \code{\link{HeatmapList}} object.  

+The data frame contains information from different aspects and different measurements are applied

+on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to

+visualize information that are stored in a data frame.

+There are not many advanced settings in this function. Users can customize the style of the heatmaps

+by constructing a \code{\link{HeatmapList}} object.

 }

 \value{

-a \code{\link{HeatmapList}} object  

-

+a \code{\link{HeatmapList}} object

 }

 \author{

-Zuguang Gu <z.gu@dkfz.de>  

-

+Zuguang Gu <z.gu@dkfz.de>

 }

 \examples{

@@ -57,5 +53,4 @@ df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], lett

                 t2 = sample(LETTERS[1:3], 10, replace = TRUE))

 plotDataFrame(df)

 plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"),

-    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")

-}

+    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")}

@@ -11,9 +11,9 @@ Visualize a data frame

 }

 \usage{

-plotDataFrame(df, overlap = 0.5, nlevel = 30, show_row_names = TRUE,

-    group = NULL, group_name = names(group), cluster_rows = TRUE,

-    cluster_columns = TRUE)

+plotDataFrame(df, overlap = 0.25, nlevel = 30, show_row_names = TRUE, show_column_names = TRUE,

+    group = NULL, group_names = names(group), main_heatmap = NULL, km = 1, split = NULL,

+    cluster_rows = TRUE, cluster_columns = TRUE, ...)

 }

 \arguments{

@@ -21,10 +21,15 @@ plotDataFrame(df, overlap = 0.5, nlevel = 30, show_row_names = TRUE,

   \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are thought under same measurement and should be grouped.}

   \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded.}

   \item{show_row_names}{whether show row names after the last heatmap if there are row names.}

+  \item{show_column_names}{whether show column names for all heatmaps}

   \item{group}{a list of index that defines the groupping}

-  \item{group_name}{names for each group}

+  \item{group_names}{names for each group}

+  \item{main_heatmap}{which group is the main heatmap}

+  \item{km}{apply k-means clustering on rows for the main heatmap}

+  \item{split}{set a splitting variable on rows for the main heatmap}

   \item{cluster_rows}{whether perform clustering on rows of the first heatmap}

   \item{cluster_columns}{whether perform clustering on columns for all heatmaps}

+  \item{...}{pass to \code{\link{draw,HeatmapList-method}} or \code{\link{make_layout,HeatmapList-method}}}

 }

 \details{

@@ -45,8 +50,12 @@ Zuguang Gu <z.gu@dkfz.de>

 }

 \examples{

-df = data.frame(x = rnorm(10), y = rnorm(10), z = rnorm(10, 10), 

-    l1 = letters[1:10], l2 = LETTERS[1:10])

+df = data.frame(matrix(rnorm(40), nrow = 10, dimnames = list(letters[1:10], letters[1:4])),

+                large = runif(10)*100,

+                t1 = sample(letters[1:3], 10, replace = TRUE),

+                matrix(runif(60), nrow = 10, dimnames = list(LETTERS[1:10], LETTERS[1:6])),

+                t2 = sample(LETTERS[1:3], 10, replace = TRUE))

 plotDataFrame(df)

-plotDataFrame(df, group = list(number = 1:3, letters = 4:5))

+plotDataFrame(df, group = list(1:4, 5, 6, 7:12, 13), group_names = c("mat1", "large", "t1", "mat2", "t2"),

+    main_heatmap = 4, km = 2, column_title = "column title", row_title = "row title")

 }

new file mode 100644

@@ -0,0 +1,52 @@

+\name{plotDataFrame}

+\alias{plotDataFrame}

+\title{

+Visualize a data frame  

+

+

+}

+\description{

+Visualize a data frame  

+

+

+}

+\usage{

+plotDataFrame(df, overlap = 0.5, nlevel = 30, show_row_names = TRUE,

+    group = NULL, group_name = names(group), cluster_rows = TRUE,

+    cluster_columns = TRUE)

+}

+\arguments{

+

+  \item{df}{a data frame}

+  \item{overlap}{how to group numeric columns. If the overlapping rate between the ranges in the current column and previous numeric column is larger than this value, the two columns are thought under same measurement and should be grouped.}

+  \item{nlevel}{If the number of levels of a character column is larger than this value, the column will be excluded.}

+  \item{show_row_names}{whether show row names after the last heatmap if there are row names.}

+  \item{group}{a list of index that defines the groupping}

+  \item{group_name}{names for each group}

+  \item{cluster_rows}{whether perform clustering on rows of the first heatmap}

+  \item{cluster_columns}{whether perform clustering on columns for all heatmaps}

+

+}

+\details{

+The data frame contains information from different aspects and different measurements are applied on the same element for each row. The \code{\link{plotDataFrame}} function provides a simple and quick way to visualize information that are stored in a data frame.  

+

+There are not many advanced settings in this function. Users can customize the style of the heatmaps by constructing a \code{\link{HeatmapList}} object.  

+

+

+}

+\value{

+a \code{\link{HeatmapList}} object  

+

+

+}

+\author{

+Zuguang Gu <z.gu@dkfz.de>  

+

+

+}

+\examples{

+df = data.frame(x = rnorm(10), y = rnorm(10), z = rnorm(10, 10), 

+    l1 = letters[1:10], l2 = LETTERS[1:10])

+plotDataFrame(df)

+plotDataFrame(df, group = list(number = 1:3, letters = 4:5))

+}