Type:	Package
Title:	Simulation, Visualization and Comparison of Tumor Evolution Data
Version:	1.1.0
Description:	Simulating, visualizing and comparing tumor clonal data by using simple commands. This aims at providing a tool to help researchers to easily simulate tumor data and analyze the results of their approaches for studying the composition and the evolutionary history of tumors.
Encoding:	UTF-8
Imports:	data.tree, purrr, reshape2, DiagrammeR, colorspace, dplyr, methods, vctrs, magrittr, stats
Depends:	R (≥ 4.00)
RoxygenNote:	7.3.2
VignetteBuilder:	knitr, rmarkdown, knitcitations, ggpubr, ggplot2
Suggests:	knitr, rmarkdown, knitcitations, ggpubr, ggplot2
NeedsCompilation:	no
LazyData:	TRUE
License:	GPL (≥ 3)
Packaged:	2025-03-27 18:44:28 UTC; aitor
Author:	Aitor Sánchez-Ferrera [cre, aut], Maitena Tellaetxe-Abete [aut], Borja Calvo [aut]
Maintainer:	Aitor Sánchez-Ferrera <aitor.sanchezf@ehu.eus>
Repository:	CRAN
Date/Publication:	2025-03-27 19:10:05 UTC

A set of 10 trios of B matrices for experimenting with the methods of GeRnika

Description

A list of lists composed by 10 trios of B matrices; a real B matrix, a B matrix got by using the one algorithm (alg1) method and another one as a result of another algorithm (alg2). These matrices can be used as examples for the methods of GeRnika.

Usage

B_mats

Format

A list of lists composed by 10 trios of B matrices.

Trio 1

B_real, B_alg1 and B_alg2 (matrices composed by 5 clones)

Trio 2

B_real, B_alg1 and B_alg2 (matrices composed by 5 clones)

Trio 3

B_real, B_alg1 and B_alg2 (matrices composed by 5 clones)

Trio 4

B_real, B_alg1 and B_alg2 (matrices composed by 5 clones)

Trio 5

B_real, B_alg1 and B_alg2 (matrices composed by 5 clones)

Trio 6

B_real, B_alg1 and B_alg2 (matrices composed by 10 clones)

Trio 7

B_real, B_alg1 and B_alg2 (matrices composed by 10 clones)

Trio 8

B_real, B_alg1 and B_alg2 (matrices composed by 10 clones)

Trio 9

B_real, B_alg1 and B_alg2 (matrices composed by 10 clones)

Trio 10

B_real, B_alg1 and B_alg2 (matrices composed by 10 clones)

Source

Local source; as a result of the Grasp and the ILS methods used for solving the Clonal Deconvolution and Evolution Problem (CDEP).

Create a Phylotree object from a B matrix.

Description

This function creates a Phylotree class object from a B matrix.

Usage

B_to_phylotree(B, labels = NA)

Arguments

Value

A Phylotree class object.

Examples

# Create a B matrix instance
# composed by 10 subpopulations of
# clones
B <- create_instance(
       n = 10, 
       m = 4, 
       k = 1, 
       selection = "neutral")$B

# Create a new 'Phylotree' object
# on the basis of the B matrix
phylotree <- B_to_phylotree(B = B)

# Generate the tags for the genes of
# the phyogenetic tree
tags <- LETTERS[1:nrow(B)]

# Create a new 'Phylotree' object
# on the basis of the B matrix and
# the list of tags
phylotree_tags <- B_to_phylotree(
                    B = B, 
                    labels = tags)

S4 class to represent phylogenetic trees.

Description

S4 class to represent phylogenetic trees.

Slots

B

A data.frame containing the square matrix that represents the ancestral relations among the clones of the phylogenetic tree.

clones

A vector representing the equivalence table of the clones in the phylogenetic tree.

genes

A vector representing the equivalence table of the genes in the phylogenetic tree.

parents

A vector representing the parents of the clones in the phylogenetic tree.

tree

A Node class object representing the phylogenetic tree.

labels

A vector representing the tags of the genes in the phylogenetic tree.

Add noise to the VAF values in an F matrix

Description

This function adds noise to the variant allele frequency (VAF) values in an F matrix, simulating the effect of sequencing errors. The noise is modeled as a negative binomial distribution for the depth of the reads and a binomial distribution for both the variant allele counts and the mismatch counts.

Usage

add_noise(F_matrix, depth, overdispersion)

Arguments

Value

A matrix containing noisy VAF values of a series of mutations in a set of samples.

Examples

# Calculate the noisy VAF values of a series of mutations in a set of samples, given the true 
# VAF values in the F matrix F_true, a depth of 30 and an overdispersion of 5

# Simulate the noise-free F matrix of a tumor with 50 clones,
# 10 samples, k = 5, following a positive selection model
F_true <- create_instance(
  n = 50,
  m = 10,
  k = 5,
  selection = "positive", 
  noisy = FALSE)$F_true

# Then we add the noise using a depth of 30 and an overdispersion of 5.
noisy_F <- add_noise(F_true, 30, 5)

Get consensus tree between two phylogenetic trees

Description

Returns a graph representing the consensus tree between two phylogenetic trees.

Usage

combine_trees(
  phylotree_1,
  phylotree_2,
  palette = GeRnika::palettes$Simpsons,
  labels = FALSE
)

Arguments

Value

a dgr_graph object representing the consensus graph between phylotree_1 phylotree_2.

Examples

# Load the predefined B matrices of the package
B_mats <- GeRnika::B_mats


B_real <- B_mats[[2]]$B_real
B_alg1 <- B_mats[[2]]$B_alg1


# Generate the tags for the genes of
# the phyogenetic tree
tags <- LETTERS[1:nrow(B_real)]


# Instantiate two \code{Phylotree} class objects on 
# the basis of the B matrices
phylotree_real <- B_to_phylotree(
                    B = B_real, 
                    labels = tags)
                    
phylotree_alg1 <- B_to_phylotree(
                    B = B_alg1, 
                    labels = tags)


# Create the consensus tree between phylotree_real
# and phylotree_alg1
consensus <- combine_trees(
               phylotree_1 = phylotree_real,
               phylotree_2 = phylotree_alg1)
               
               
# Render the consensus tree
DiagrammeR::render_graph(consensus)


# Load another palette
palette_1 <- GeRnika::palettes$Lancet


# Create the consensus tree between phylotree_real
# and phylotree_alg1 using tags and another palette
consensus_tag <- combine_trees(
                   phylotree_1 = phylotree_real, 
                   phylotree_2 = phylotree_alg1,
                   palette = palette_1,
                   labels = TRUE)


# Render the consensus tree using tags and the
# selected palette
DiagrammeR::render_graph(consensus_tag)

Create tumor phylogenetic tree topology

Description

This function generates a mutation matrix (B matrix) for a tumor phylogenetic tree with a given number of nodes. This matrix represents the topology and it is created randomly, with the probability of a node to be chosen as a parent of a new node being proportional to the number of its ascendants raised to the power of a constant 'k'.

Usage

create_B(n, k)

Arguments

Value

A square matrix representing the mutation relationships between the nodes in the phylogenetic tree. Each row corresponds to a node, and each column corresponds to a mutation. The value at the i-th row and j-th column is 1 if the i-th node has the j-th mutation, and 0 otherwise.

Examples

# Create a mutation matrix for a phylogenetic tree with 10 nodes and k = 2
B <- create_B(10, 2)

Calculate the variant allele frequency (VAF) values in a set of samples

Description

This method generates the F matrix that contains the mutation frequency values of a series of mutations in a collection of tumor biopsies or samples.

Usage

create_F(U, B, heterozygous = TRUE)

Arguments

Value

A matrix containing the VAF values of a series of mutations in a set of samples.

Examples

# Create random topology with 10 nodes and k = 2
B <- create_B(10, 2)

# Create U matrix with parameter m=4 and "positive" selection
U <- create_U(B = B, m = 4, selection = "positive")

# Then we compute the F matrix for a heterozygous tumor
F <- create_F(U = U, B = B, heterozygous = TRUE)

Calculate tumor clone frequencies in samples

Description

This function calculates the frequencies of each clone in a set of samples, given the global clone proportions in the tumor and their spatial distribution.

Usage

create_U(B, m, selection, n_cells = 100)

Arguments

Value

A matrix where each row corresponds to a sample, and each column corresponds to a clone. The value at the i-th row and j-th column is the frequency of the j-th clone in the i-th sample.

Examples

# Create random topology with 20 nodes and k = 3
B <- create_B(20, 3)

# Create U matrix with parameter m=4 and "positive" selection
U <- create_U(B = B, m = 4, selection = "positive")

Create a tumor phylogenetic tree instance

Description

This function generates a tumor phylogenetic tree instance, composed by a mutation matrix (B matrix), a matrix of true variant allele frequencies (F_true), a matrix of noisy variant allele frequencies (F), and a matrix of clone frequencies in samples (U).

Usage

create_instance(
  n,
  m,
  k,
  selection,
  noisy = TRUE,
  depth = 30,
  seed = Sys.time()
)

Arguments

Details

The B matrix is a square matrix representing the mutation relationships between the clones in the tumor, or, in other words, it represents the topology of the phylogenetic tree. The F_true matrix represents the true variant allele frequencies of the mutations present in the tumor in a set of samples. The F matrix represents the noisy variant allele frequencies of the mutations in the same set of samples. The U matrix represents the frequencies of the clones in the tumor in the set of samples.

Value

A list containing four elements: 'F', a matrix representing the noisy frequencies of each mutation in each sample; 'B', a matrix representing the mutation relationships between the clones in the tumor; 'U', a matrix that represents the frequencies of the clones in the tumor in the set of samples; and 'F_true', a matrix representing the true frequencies of each mutation in each sample.

Examples

# Create an instance of a tumor with 10 clones,
# 4 samples, k = 1, neutral evolution and
# added noise with depth = 500
I1 <- create_instance(
  n = 10,
  m = 4,
  k = 1,
  selection = "neutral",
  depth = 500)
  

# Create an instance of a tumor with 50 clones,
# 10 samples, k = 5, positive selection and
# added noise with depth = 500
I2 <- create_instance(
  n = 50,
  m = 10,
  k = 5,
  selection = "positive", 
  noisy = TRUE,
  depth = 500)
  
  
# Create an instance of a tumor with 100 clones,
# 25 samples, k = 0, positive selection without 
# noise
I3 <- create_instance(
  n = 100,
  m = 25,
  k = 0,
  selection = "positive", 
  noisy = FALSE)

Create a Phylotree object

Description

This is the general constructor of the Phylotree S4 class.

Usage

create_phylotree(B, clones, genes, parents, tree, labels = NA)

Arguments

Value

A Phylotree class object.

Examples

# Create a B matrix instance
# composed by 10 subpopulations of
# clones
B <- create_instance(
       n = 10, 
       m = 4, 
       k = 1, 
       selection = "neutral")$B


# Create a new 'Phylotree' object
# on the basis of the B matrix
phylotree1 <- B_to_phylotree(B = B)


# Create a new 'Phylotree' object
# with the general constructor of
# the class
phylotree2 <- create_phylotree(
                B = B, 
                clones = phylotree1@clones, 
                genes = phylotree1@genes, 
                parents = phylotree1@parents, 
                tree = phylotree1@tree)


# Generate the tags for the genes of
# the phyogenetic tree
tags <- LETTERS[1:nrow(B)]

 
# Create a new 'Phylotree' object
# with the general constructor of
# the class using tags
phylotree_tags <- create_phylotree(
                    B = B, 
                    clones = phylotree1@clones, 
                    genes = phylotree1@genes, 
                    parents = phylotree1@parents, 
                    tree = phylotree1@tree, 
                    labels = tags)

Check if two phylogenetic trees are equal

Description

Checks wether two phylogenetic trees are equivalent or not.

Usage

equals(phylotree_1, phylotree_2)

Arguments

Value

A boolean, TRUE if they are equal and FALSE if not.

Examples

# Load the predefined B matrices of the package
B_mats <- GeRnika::B_mats


B_real <- B_mats[[2]]$B_real
B_alg1 <- B_mats[[2]]$B_alg1


# Instantiate two \code{Phylotree} class objects on 
# the basis of the B matrices
phylotree_real <- B_to_phylotree(
                    B = B_real)
                    
phylotree_alg1 <- B_to_phylotree(
                    B = B_alg1)


equals(phylotree_real, phylotree_alg1)

Find the set of common subtrees between two phylogenetic trees

Description

Plots the common subtrees between two phylogenetic trees and prints the information about their similarities and their differences.

Usage

find_common_subtrees(phylotree_1, phylotree_2, labels = FALSE)

Arguments

Value

A plot of the common subtrees between two phylogenetic trees and the information about the distance between them based on their independent and common edges.

Examples

# Load the predefined B matrices of the package
B_mats <- GeRnika::B_mats


B_real <- B_mats[[2]]$B_real
B_alg1 <- B_mats[[2]]$B_alg1


# Generate the tags for the genes of
# the phyogenetic tree
tags <- LETTERS[1:nrow(B_real)]


# Instantiate two Phylotree class objects on 
# the basis of the B matrices using tags
phylotree_real <- B_to_phylotree(
                    B = B_real, 
                    labels = tags)
                    
phylotree_alg1 <- B_to_phylotree(
                    B = B_alg1, 
                    labels = tags)


# find the set of common subtrees between both 
# phylogenetic trees
find_common_subtrees(
  phylotree_1 = phylotree_real, 
  phylotree_2 = phylotree_alg1)


# find the set of common subtrees between both
# phylogenetic trees using tags
find_common_subtrees(
  phylotree_1 = phylotree_real, 
  phylotree_2 = phylotree_alg1, 
  labels = TRUE)

Palettes for the methods of GeRnika

Description

A data.frame containing 3 default palettes for the parameters used in the methods of GeRnika.

Usage

palettes

Format

A data.frame containing 3 palettes.

Lancet

#0099B444, #AD002A77, #42B540FF

NEJM

#FFDC9177, #7876B188, #EE4C97FF

Simpsons

#FED43966, #FD744688, #197EC0FF

Source

Lancet, NEJM and The Simpsons palettes; inspired by the plots in Lancet journals, the plots in the New England Journal of Medicine and the colors used in the TV show The Simpsons, respectively.

Plot a Phylotree object.

Description

Plot a Phylotree object.

Usage

plot(object, labels = FALSE)

## S4 method for signature 'Phylotree'
plot(object, labels = FALSE)

Arguments

Plot a phylogenetic tree with proportional node sizes and colors

Description

This function plots a phylogenetic tree with nodes sized and colored according to the proportions of each clone. If a matrix of proportions is provided, multiple phylogenetic trees will be plotted, each corresponding to a row of proportions.

Usage

plot_proportions(phylotree, proportions, labels = FALSE)

Arguments

Value

A graph representing the phylogenetic tree, with node sizes and colors reflecting clone proportions.

Examples

# Create an instance
# composed by 5 subpopulations of clones
# and 4 samples
instance <- create_instance(
       n = 5, 
       m = 4, 
       k = 1, 
       selection = "neutral")
       
# Extract its associated B matrix
B <- instance$B

# Create a new 'Phylotree' object
# on the basis of the B matrix
phylotree <- B_to_phylotree(B = B)

# Generate the tags for the genes of
# the phyogenetic tree
tags <- LETTERS[1:nrow(B)]

# Plot the phylogenetic tree taking
# into account the proportions of the
# previously generated instance
plot_proportions(phylotree, instance$U, labels=TRUE)