knitr, rmarkdown, testthat, svglite, vdiffr, gridExtra,
devtools, prettydoc, ggbeeswarm, dplyr, magrittr, readr,
stringr, withr

c(
person("Claus O.", "Wilke", , "wilke@austin.utexas.edu", c("cre", "aut")),
person("RStudio", role = c("cph"), comment = "Copyright for ggplot2 code copied to ggridges"))
Ridgeline plots provide a convenient way of visualizing changes in distributions over
time or space. This package enables the creation of such plots in 'ggplot2'.
'data.R' 'ggridges.R' 'geoms.R' 'geomsv.R' 'geoms-gradient.R'
'scale-cyclical.R' 'stats.R' 'theme.R' 'utils_ggplot2.R'
'utils.R'
Claus O. Wilke [cre, aut],
RStudio [cph] (Copyright for ggplot2 code copied to ggridges)

Ridgeline plots provide a convenient way of visualizing changes in distributions over time or space. This package enables the creation of such plots in 'ggplot2'.

covr, dplyr, gridExtra, ggplot2movies, DAAG, forcats, knitr,
rmarkdown, testthat, vdiffr, viridis
'data.R' 'ggridges.R' 'geoms.R' 'geomsv.R' 'geoms-gradient.R'
'geom-density-line.R' 'position.R' 'scale-.R'
'scale-cyclical.R' 'scale-point.R' 'scale-vline.R' 'stats.R'
'theme.R' 'utils_ggplot2.R' 'utils.R'

covr, dplyr, patchwork, ggplot2movies, forcats, knitr,
rmarkdown, testthat, vdiffr
'data.R' 'ggridges.R' 'geoms.R' 'geomsv.R' 'geoms-gradient.R'
'geom-density-line.R' 'position.R' 'scale-cyclical.R'
'scale-point.R' 'scale-vline.R' 'stats.R' 'theme.R'
'utils_ggplot2.R' 'utils.R'

The risk plot may be one of the most commonly used figures in
tumor genetic data analysis. We can conclude the following two points:
Comparing the prediction results of the model with the real survival situation
to see whether the survival rate of the high-risk group is lower than that of the
low-level group, and whether the survival time of the high-risk group is
shorter than that of the low-risk group. The other is to compare the heat
map and scatter plot to see the correlation between the predictors and the
outcome.
ggplot2, survival, egg, do, set, cutoff, fastStat, grid, rms,
nomogramFormula