| Title: | Generate Cofeature Matrices |
| Version: | 1.1.1 |
| Description: | Generate cofeature (feature by sample) matrices. The package utilizes ggplot2::geom_tile() to generate the matrix allowing for easy additions from the base matrix. |
| Depends: | R (≥ 3.1.0) |
| Imports: | ggplot2 (≥ 1.0.0), dplyr (≥ 0.4.3), lazyeval (≥ 0.1.10), tibble |
| URL: | https://github.com/tinyheero/cofeatureR |
| BugReports: | https://github.com/tinyheero/cofeatureR/issues |
| License: | GPL-3 |
| LazyData: | true |
| RoxygenNote: | 6.0.1 |
| Suggests: | testthat |
| NeedsCompilation: | no |
| Packaged: | 2018-06-24 14:58:23 UTC; fongchun |
| Author: | Fong Chun Chan [aut, cre] |
| Maintainer: | Fong Chun Chan <fongchunchan@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2018-06-24 15:09:05 UTC |
cofeatureR: Generate Cofeature Matrices
Description
Generate cofeature (feature by sample) matrices. The package utilizes ggplot2::geom_tile to generate the matrix allowing for easy customization of additions from the base matrix.
Add tiles to the ggplot2
Description
Add tiles to the ggplot2
Usage
add_tiles(p1, in.df, tile.col, missing.fill.col, tile.border.size)
Arguments
p1 |
Existing ggplot2 |
in.df |
A 3 column (feature, sampleID, type) data.frame object |
tile.col |
Border color of each cell. If not set, no border color is used. |
missing.fill.col |
Color of the cell that has missing values |
tile.border.size |
Integer to indicate the size of the tile borders. |
Plot a Cofeature Matrix
Description
Generates a ggplot2::geom_tile plot of features by sample. It is able to deal with multiple types affecting the same sample.
Usage
plot_cofeature_mat(in.df, feature.order, sample.id.order, fill.colors,
type.display.mode = c("multiple", "single"), type.order, tile.col = NA,
rotate.x.labels, missing.fill.col, dot.flag = FALSE, dot.size,
tile.flag = TRUE, drop.x = FALSE, tile.border.size = 1)
Arguments
in.df |
A 3 column (feature, sampleID, type) data.frame object |
feature.order |
character vector indicating the order of the features in the final plot on the y-axis. If not set, then function will set it automatically |
sample.id.order |
character vector indicating the order of the samples in the final plot on the x-axis. If not set, then function will set it automatically |
fill.colors |
character vector indicating the colors of the different "types". The names should be the types with the value being the color |
type.display.mode |
Specify whether multiple or a single feature type can appear in the same feature/sample cell |
type.order |
Specify the "priority" of the feature types. This only has an effect when type.display.mode is set to single. |
tile.col |
Border color of each cell. If not set, no border color is used. |
rotate.x.labels |
Rotate the x-axes labels by a certain degree |
missing.fill.col |
Color of the cell that has missing values |
dot.flag |
Boolean to turn on/off dots (dot.flag) |
dot.size |
Column name indicating the size of the dots. Only takes effect if dot.flag is TRUE. |
tile.flag |
Boolean to turn on/off tiles (tile.flag) |
drop.x |
Boolean to drop levels (from a factor) in the x dimension. |
tile.border.size |
Integer to indicate the size of the tile borders. |
Examples
## Not run:
v1 <- c("RCOR1", "NCOR1", "LCOR", "RCOR1", "RCOR1", "RCOR1", "RCOR1")
v2 <- c("sampleA", "sampleC", "sampleB", "sampleC", "sampleA", "sampleC", "sampleC")
v3 <- c("Deletion", "Deletion", "SNV", "Rearrangement", "SNV", "Rearrangement", "SNV")
v4 <- c(0.05, 0.5, 0.25, 0.01, 0.03, 0.24, 0.89)
v5 <- c(1, 2, 1, 1, 2, 2, 1)
feature.order <- c("RCOR1", "NCOR1", "LCOR")
sample.id.order <- c("sampleA", "sampleB", "sampleC")
in.df <- dplyr::data_frame(feature = v1, sampleID = v2, type = v3,
p_value = -log10(v4), dir_flag = v5)
fill.colors <- c("Deletion" = "Blue", "Rearrangement" = "Green", "SNV" = "Red")
plot_cofeature_mat(in.df)
# With black tile color
plot_cofeature_mat(in.df, tile.col = "black")
# Fill in missing values with a lightgrey color
plot_cofeature_mat(in.df, tile.col = "black", missing.fill.col = "lightgrey")
# Rotate x-axes labels by 90 degrees
plot_cofeature_mat(in.df, rotate.x.labels = 90)
# Specify order of features, samples, and colors
plot_cofeature_mat(in.df, feature.order, sample.id.order,
fill.colors = fill.colors)
# Specify each cell can only have one "feature type"
plot_cofeature_mat(in.df, feature.order, sample.id.order, fill.colors = fill.colors,
type.display.mode = "single")
# Specify the specific priority of the "feature type" for cells with
# multiple features
plot_cofeature_mat(in.df, feature.order, sample.id.order, fill.colors = fill.colors,
type.display.mode = "single", type.order = c("Rearrangement", "SNV", "Deletion"))
# Add dots to tiles for an additional layer of information
plot_cofeature_mat(in.df, dot.size = "p_value")
# Only display dots
plot_cofeature_mat(in.df, dot.flag = TRUE, dot.size = "p_value",
tile.flag = FALSE)
# Samples will not be dropped
sample.id.order.new <- c("sampleA", "sampleB", "sampleC", "sampleD")
plot_cofeature_mat(in.df, tile.col = "black",
sample.id.order = sample.id.order.new)
# Samples can be dropped by setting drop.x = TRUE
plot_cofeature_mat(in.df, tile.col = "black",
sample.id.order = sample.id.order.new, drop.x = TRUE)
## End(Not run)