This commit is contained in:
2022-02-12 10:42:10 +01:00
3 changed files with 21 additions and 9 deletions
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@@ -1,4 +1,4 @@
ggheatmap<-function(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_group=NULL, scale="none"){ ggheatmap<-function(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_group=NULL, scale="none",color="#FFFFFF00"){
if (is.null(x)){x=colnames(df)[1]} if (is.null(x)){x=colnames(df)[1]}
if (is.null(y)){y=colnames(df)[2]} if (is.null(y)){y=colnames(df)[2]}
if (is.null(value)){value=colnames(df)[3]} if (is.null(value)){value=colnames(df)[3]}
@@ -39,5 +39,9 @@ ggheatmap<-function(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_gro
df %>% df %>%
ggplot(aes(VarX, VarY, fill=Value))+ ggplot(aes(VarX, VarY, fill=Value))+
labs(x=x, y=y)+ labs(x=x, y=y)+
theme_heatmap() geom_tile(aes(fill=Value), color=color)+
scale_fill_gradientn(colors=col2(200))+
theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust=0.5),
panel.background = element_blank(),
axis.ticks = element_blank())
} }
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@@ -2,7 +2,7 @@
\alias{ggheatmap} \alias{ggheatmap}
\title{ggheatmap} \title{ggheatmap}
\usage{ \usage{
ggheatmap(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_group=NULL, scale="none") ggheatmap(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_group=NULL, scale="none", color="#FFFFFF00")
} }
\arguments{ \arguments{
\item{df}{A data frame in "long" format.} \item{df}{A data frame in "long" format.}
@@ -12,6 +12,7 @@ ggheatmap(df, x=NULL, y=NULL, value=NULL, grouping="mean", exclude_group=NULL, s
\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".} \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".}
\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.} \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.}
\item{scale}{Escales (z-score) by "rows" or "cols" if diferent of "none" (default).} \item{scale}{Escales (z-score) by "rows" or "cols" if diferent of "none" (default).}
\item{color}{The color of the lines of geom_tile (the border). By default, its transparent.}
} }
\description{ \description{
Generates a heatmap using ggplot for a dataframe. 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
Now we are ready to install CitFuns package: Now we are ready to install CitFuns package:
```{r, eval=F} ```{r, eval=F}
devtools::install_git("https://git.ratg.cat/marcelcosta/CitFuns.git") devtools::install_git("https://git.ratg.cat/marcelcosta/CitFuns.git", build_vignettes = T)
``` ```
## Update ## Update
@@ -123,6 +123,13 @@ By default, ggcorrplot converts the p-value into *star* significance equivalence
ggcorrplot(df, var = "Cyt", value = "Value", color = "white", stat="pval") ggcorrplot(df, var = "Cyt", value = "Value", color = "white", stat="pval")
``` ```
ggcorrplot uses "pearson" by default to obtain a correlation coeficient, although "spearman" is also available.
```{r, fig.width=5, fig.height=4}
ggcorrplot(df, var = "Cyt", value = "Value", color = "white", stat="pval", method="spearman")
```
Finally, you can show only the upper part or the lower part of the specular matrix. Finally, you can show only the upper part or the lower part of the specular matrix.
```{r, fig.width=5, fig.height=4} ```{r, fig.width=5, fig.height=4}