Help for package tcgaViz

Title:

Visualization Tool for the Cancer Genome Atlas Program (TCGA)

Version:

1.0.2

Description:

Differential analysis of tumor tissue immune cell type abundance based on RNA-seq gene-level expression from The Cancer Genome Atlas (TCGA; https://pancanatlas.xenahubs.net) database.

License:

GPL-3

Depends:

R (≥ 2.10)

Imports:

config, data.table, dplyr, DT, ggplot2, ggpubr, golem, grDevices, magrittr, methods, plotly, readr, reshape2, rlang, rstatix, scales, shiny, shinyFeedback, shinyjs, stats, stringr, tidyr, tidyselect, utils

Suggests:

covr, knitr, rmarkdown, spelling, testthat

VignetteBuilder:

knitr

Encoding:

UTF-8

Language:

en-US

LazyData:

false

RoxygenNote:

7.2.3

NeedsCompilation:

Packaged:

2023-04-04 13:46:18 UTC; rstudio

Author:

Etienne Camenen [aut, cre], Gilles Marodon [aut], Nicolas Aubert [aut]

Maintainer:

Etienne Camenen <etienne.camenen@gmail.com>

Repository:

CRAN

Date/Publication:

2023-04-04 15:40:02 UTC

tcgaViz: Visualization Tool for the Cancer Genome Atlas Program (TCGA)

Description

Differential analysis of tumor tissue immune cell type abundance based on RNA-seq gene-level expression from The Cancer Genome Atlas (TCGA; <https://pancanatlas.xenahubs.net>) database.

Author(s)

Maintainer: Etienne Camenen etienne.camenen@gmail.com

Authors:

Gilles Marodon
Nicolas Aubert

Corrected Wilcoxon tests

Description

Displays stars for each cell type corresponding to the significance level of two mean comparison tests between expression levels (high or low) with multiple correction.

Usage

calculate_pvalue(
  x,
  method_test = "wilcox_test",
  method_adjust = "BH",
  p_threshold = 0.05
)

Arguments

x

object from convert2biodata() for a dataframe containing columns named high (logical), cell_type (factor) and value (float).

method_test

character for the choice of the statistical test among 't_test' or 'wilcox_test'.

method_adjust

character for the choice of the multiple correction test among 'BH', 'bonferroni', 'BY', 'fdr', 'hochberg', 'holm', 'hommel', 'none'

p_threshold

float for the significativity threshold of the P-value.

Value

rstatix_test object for a table with cell types in the row and P-values, corrections and other statistics in the column.

Examples

data(tcga)
(df <- convert2biodata(
    algorithm = "Cibersort_ABS",
    disease = "breast invasive carcinoma",
    tissue = "Primary Tumor",
    gene_x = "ICOS"
))

calculate_pvalue(df)

calculate_pvalue(
    df,
    method_test = "t_test",
    method_adjust = "bonferroni",
    p_threshold = 0.01
)

Format biological data

Description

Merges gene and cell datasets with the same TCGA sample identifiers, splits samples according to the expression levels of a selected gene into two categories (below or above average) and formats into a 3-column data frame: gene expression levels, cell types, and gene expression values.

Usage

convert2biodata(algorithm, disease, tissue, gene_x, stat = "mean", path = ".")

Arguments

algorithm

character for the algorithm used to estimate the distribution of cell type abundance among : 'Cibersort', 'Cibersort_ABS', 'EPIC', 'MCP_counter', 'Quantiseq', 'Timer', 'Xcell', 'Xcell (2)' and 'Xcell64'.

disease

character for the type of TCGA cancer (see the list in extdata/disease_names.csv).

tissue

character for the type of TCGA tissue among : 'Additional - New Primary', 'Additional Metastatic', 'Metastatic', 'Primary Blood Derived Cancer - Peripheral Blood', 'Primary Tumor', 'Recurrent Tumor', 'Solid Tissue Normal'

gene_x

character for the gene selected in the differential analysis (see the list in extdata/gene_names.csv).

stat

character for the statistic to be chosen among "mean", "median" or "quantile".

path

character for the path name of the tcga dataset.

Value

data frame with the following columns:

high (logical): the expression levels of a selected gene, TRUE for below or FALSE for above average.
cells (factor): cell types.
value (float): the abundance estimation of the cell types.

Examples

data(tcga)
(convert2biodata(
    algorithm = "Cibersort_ABS",
    disease = "breast invasive carcinoma",
    tissue = "Primary Tumor",
    gene_x = "ICOS"
))

Format biological data

Description

Usage

convert_biodata(
  genes,
  cells,
  select = colnames(genes)[3],
  stat = "mean",
  disease = NULL,
  tissue = NULL
)

Arguments

genes

data frame whose first two columns contain identifiers and the others float values.

cells

data frame whose first two columns contain identifiers and the others float values.

select

character for a column name in genes.

stat

character for the statistic to be chosen among "mean", "median" or "quantile".

disease

character for the type of TCGA cancer (see the list in extdata/disease_names.csv).

tissue

Details

disease and tissue arguments should be displayed in the title of plot.biodata() only if the genes argument does not already have them in its attributes.

Value

data frame with the following columns:

high (logical): the expression levels of a selected gene, TRUE for below or FALSE for above average.
cells (factor): cell types.
value (float): the abundance estimation of the cell types.

Examples

data(tcga)
(df_formatted <- convert_biodata(tcga$genes, tcga$cells$Cibersort, "ICOS"))

Distribution plot

Description

Distribution plot of cell subtypes according to the expression level (high or low) of a selected gene.

Usage

## S3 method for class 'biodata'
plot(
  x,
  type = "violin",
  dots = FALSE,
  title = NULL,
  xlab = NULL,
  ylab = NULL,
  stats = NULL,
  draw = TRUE,
  axis.text.x = element_text(size = 10),
  axis.text.y = element_text(size = 8),
  cex.lab = 12,
  cex.main = 16,
  col = (scales::hue_pal())(length(unique(x$cell_type))),
  axis.title.x = element_text(size = cex.lab, face = "bold.italic", vjust = -0.5),
  axis.title.y = element_text(size = cex.lab, face = "bold.italic", vjust = -0.5),
  plot.title = element_text(size = cex.main, face = "bold", vjust = 1, hjust = 0.5),
  plot.margin = unit(c(0, 0, 0, -0.5), "cm"),
  ...
)

Arguments

x

object from convert2biodata() for a dataframe containing columns named high (logical), cell_type (factor) and value (float).

type

character for the type of plot to be chosen among "violin" or "boxplot".

dots

boolean to add all points to the graph.

title

character for the title of the plot.

xlab

character for the name of the X axis label.

ylab

character for the name of the Y axis label.

stats

object from calculate_pvalue().

draw

bolean to plot the graph.

axis.text.x

tick labels along axes (element_text()). Specify all axis tick labels (axis.text), tick labels by plane (using axis.text.x or axis.text.y), or individually for each axis (using axis.text.x.bottom, axis.text.x.top, axis.text.y.left, axis.text.y.right). ⁠axis.text.*.*⁠ inherits from ⁠axis.text.*⁠ which inherits from axis.text, which in turn inherits from text

axis.text.y

cex.lab

numerical value giving the amount by which x and y plotting labels should be magnified relative to the default.

cex.main

numerical value giving the amount by which main plotting title should be magnified relative to the default.

col

character for the specification for the default plotting color. See section 'Color Specification' in graphics::par().

axis.title.x

labels of axes (element_text()). Specify all axes' labels (axis.title), labels by plane (using axis.title.x or axis.title.y), or individually for each axis (using axis.title.x.bottom, axis.title.x.top, axis.title.y.left, axis.title.y.right). ⁠axis.title.*.*⁠ inherits from ⁠axis.title.*⁠ which inherits from axis.title, which in turn inherits from text

axis.title.y

plot.title

plot title (text appearance) (element_text(); inherits from title) left-aligned by default

plot.margin

margin around entire plot (unit with the sizes of the top, right, bottom, and left margins)

...

arguments to pass to ggplot2::theme().

Value

No return value, called for side effects

Examples

library("ggplot2")
data(tcga)
(df <- convert2biodata(
    algorithm = "Cibersort_ABS",
    disease = "breast invasive carcinoma",
    tissue = "Primary Tumor",
    gene_x = "ICOS"
))

plot(df)
stats <- calculate_pvalue(df)
plot(
    df,
    stats = stats,
    type = "boxplot",
    dots = TRUE,
    xlab = "Expression level of the 'ICOS' gene by cell type",
    ylab = "Percent of relative abundance\n(from the Cibersort_ABS algorithm)",
    title = "Differential analysis of tumor tissue immune cell type abundance
    based on RNASeq gene-level expression from The Cancer Genome Atlas
    (TCGA) database",
    axis.text.y = element_text(size = 8, hjust = 0.5),
    plot.title =  element_text(face = "bold", hjust = 0.5)
)

Run the Shiny Application

Description

Runs a Shiny application. This function normally does not return; interrupt R to stop the application (usually by pressing Ctrl+C or Esc).

Usage

run_app(
  onStart = NULL,
  options = list(),
  enableBookmarking = NULL,
  uiPattern = "/",
  ...
)

Arguments

onStart

A function that will be called before the app is actually run. This is only needed for shinyAppObj, since in the shinyAppDir case, a global.R file can be used for this purpose.

options

Named options that should be passed to the runApp call (these can be any of the following: "port", "launch.browser", "host", "quiet", "display.mode" and "test.mode"). You can also specify width and height parameters which provide a hint to the embedding environment about the ideal height/width for the app.

enableBookmarking

Can be one of "url", "server", or "disable". The default value, NULL, will respect the setting from any previous calls to enableBookmarking(). See enableBookmarking() for more information on bookmarking your app.

uiPattern

A regular expression that will be applied to each GET request to determine whether the ui should be used to handle the request. Note that the entire request path must match the regular expression in order for the match to be considered successful.

...

arguments to pass to golem_opts. See ?golem::get_golem_options for more details.

Details

For more information about this function, please take a look at https://CRAN.R-project.org/package=golem/vignettes/c_deploy.html.

Value

An object that represents the app.

Examples

if (interactive()) {
# Start app in the current working directory
run_app()

# Start app in a subdirectory called myapp
run_app("myapp")
}

Biological data

Description

A list of biological data: RNASeq data, phenotypic metadata and cell abundance.

Usage

data(tcga)

Details

genes: RNASeq from The Cancer Genome Atlas (TCGA) database.
phenotypes: Metadata from the TCGA database containing sample ID, sample type ID, sample type and primary disease.
cells: Abundance estimates of cell types

Note

Subset of thirty samples of invasive breast carcinoma data from primary tumor tissue. The cell type data are from a subset generated by the Cibersort_ABS algorithm (https://cibersortx.stanford.edu). For the complete dataset, please use:

path <- system.file("extdata", package = "tcgaViz")
load(file.path(path, "tcga.rda"))

Source

dataset: gene expression RNAseq - Batch effects normalized mRNA data
hub: https://pancanatlas.xenahubs.net
cohort: TCGA Pan-Cancer (PANCAN)
dataset ID: EB++AdjustPANCAN_IlluminaHiSeq_RNASeqV2.geneExp.xena
download: https://tcga-pancan-atlas-hub.s3.us-east-1.amazonaws.com/download/EB%2B%2BAdjustPANCAN_IlluminaHiSeq_RNASeqV2.geneExp.xena.gz (full metadata)
samples: 11060
version: 2016-12-29
type of data: gene expression RNAseq
unit: log2(norm_value+1)
raw data: https://www.synapse.org/#!Synapse:syn4976369.3
input data format: ROWs (identifiers) x COLUMNs (samples) (i.e. genomicMatrix)

Examples

data(tcga)
(df <- convert2biodata(
    algorithm = "Cibersort_ABS",
    disease = "breast invasive carcinoma",
    tissue = "Primary Tumor",
    gene_x = "ICOS"
))
(stats <- calculate_pvalue(df))

plot(df, stats = stats)

tcgaViz: Visualization Tool for the Cancer Genome Atlas Program (TCGA)

Description

Author(s)

See Also

Corrected Wilcoxon tests

Description

Usage

Arguments

Value

Examples

Format biological data

Description

Usage

Arguments

Value

Examples

Format biological data

Description

Usage

Arguments

Details

Value

Examples

Distribution plot

Description

Usage

Arguments

Value

Examples

Run the Shiny Application

Description

Usage

Arguments

Details

Value

Examples

Biological data

Description

Usage

Details

Note

Source

Examples