Merge branch 'main' of https://git.ratg.cat/marcelcosta/CitFuns into main
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@@ -1,4 +1,4 @@
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ggheatmap<-function(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_group=NULL, scale="none"){
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ggheatmap<-function(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_group=NULL, scale="none",color="#FFFFFF00"){
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if (is.null(x)){x=colnames(df)[1]}
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if (is.null(x)){x=colnames(df)[1]}
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if (is.null(y)){y=colnames(df)[2]}
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if (is.null(y)){y=colnames(df)[2]}
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if (is.null(value)){value=colnames(df)[3]}
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if (is.null(value)){value=colnames(df)[3]}
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@@ -39,5 +39,9 @@ ggheatmap<-function(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_gro
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df %>%
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df %>%
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ggplot(aes(VarX, VarY, fill=Value))+
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ggplot(aes(VarX, VarY, fill=Value))+
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labs(x=x, y=y)+
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labs(x=x, y=y)+
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theme_heatmap()
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geom_tile(aes(fill=Value), color=color)+
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scale_fill_gradientn(colors=col2(200))+
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theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust=0.5),
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panel.background = element_blank(),
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axis.ticks = element_blank())
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}
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}
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+2
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@@ -2,7 +2,7 @@
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\alias{ggheatmap}
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\alias{ggheatmap}
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\title{ggheatmap}
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\title{ggheatmap}
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\usage{
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\usage{
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ggheatmap(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_group=NULL, scale="none")
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ggheatmap(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_group=NULL, scale="none", color="#FFFFFF00")
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}
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}
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\arguments{
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\arguments{
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\item{df}{A data frame in "long" format.}
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\item{df}{A data frame in "long" format.}
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@@ -12,6 +12,7 @@ ggheatmap(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_group=NULL, s
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\item{grouping}{The function that will be used to group if there is more than one observation for each X-Y combination. "mean" or "median" are posible, defaulting to "mean".}
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\item{grouping}{The function that will be used to group if there is more than one observation for each X-Y combination. "mean" or "median" are posible, defaulting to "mean".}
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\item{exclude_group}{If you want to exclude columns from grouping, you can introduce a character vector here. Useful if you want to facet the plot.}
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\item{exclude_group}{If you want to exclude columns from grouping, you can introduce a character vector here. Useful if you want to facet the plot.}
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\item{scale}{Escales (z-score) by "rows" or "cols" if diferent of "none" (default).}
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\item{scale}{Escales (z-score) by "rows" or "cols" if diferent of "none" (default).}
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\item{color}{The color of the lines of geom_tile (the border). By default, its transparent.}
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}
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}
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\description{
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\description{
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Generates a heatmap using ggplot for a dataframe.
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Generates a heatmap using ggplot for a dataframe.
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@@ -28,7 +28,7 @@ You will also need [Git](https://git-scm.com/downloads) installed in your comput
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Now we are ready to install CitFuns package:
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Now we are ready to install CitFuns package:
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```{r, eval=F}
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```{r, eval=F}
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devtools::install_git("https://git.ratg.cat/marcelcosta/CitFuns.git")
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devtools::install_git("https://git.ratg.cat/marcelcosta/CitFuns.git", build_vignettes = T)
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```
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```
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## Update
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## Update
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@@ -123,6 +123,13 @@ By default, ggcorrplot converts the p-value into *star* significance equivalence
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ggcorrplot(df, var = "Cyt", value = "Value", color = "white", stat="pval")
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ggcorrplot(df, var = "Cyt", value = "Value", color = "white", stat="pval")
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```
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```
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ggcorrplot uses "pearson" by default to obtain a correlation coeficient, although "spearman" is also available.
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```{r, fig.width=5, fig.height=4}
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ggcorrplot(df, var = "Cyt", value = "Value", color = "white", stat="pval", method="spearman")
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```
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Finally, you can show only the upper part or the lower part of the specular matrix.
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Finally, you can show only the upper part or the lower part of the specular matrix.
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```{r, fig.width=5, fig.height=4}
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```{r, fig.width=5, fig.height=4}
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