Package 'fbar'

Title: An Extensible Approach to Flux Balance Analysis
Description: A toolkit for Flux Balance Analysis and related metabolic modeling techniques. Functions are provided for: parsing models in tabular format, converting parsed metabolic models to input formats for common linear programming solvers, and evaluating and applying gene-protein-reaction mappings. In addition, there are wrappers to parse a model, select a solver, find the metabolic fluxes, and return the results applied to the original model. Compared to other packages in this field, this package puts a much heavier focus on providing reusable components that can be used in the design of new implementation of new techniques, in particular those that involve large parameter sweeps. For a background on the theory, see What is Flux Balance Analysis <doi:10.1038/nbt.1614>.
Authors: Max Conway [aut, cre]
Maintainer: Max Conway <[email protected]>
License: GPL-3
Version: 0.6.0
Built: 2025-02-09 03:45:07 UTC
Source: https://github.com/maxconway/fbar

Help Index

Decompose a metabolite table into the metabolite stub itself and the compartment it is in

Description

Decompose a metabolite table into the metabolite stub itself and the compartment it is in

Usage

decompose_metabolites(
  met_table,
  compartment_regex = "(\\[[a-zA-Z0-9]+]$)|(_[a-zA-Z]$)"
)

Arguments

met_table

A metabolite table, with one column, met
compartment_regex

Regular expression to identify compartments in model

Value

a metabolite table with the columns chemical and compartment

Examples

data(ecoli_core)

mod <- reactiontbl_to_expanded(ecoli_core)

decompose_metabolites(mod$mets)

recompose_metabolites(decompose_metabolites(mod$mets))

A small E. coli model, created from a number of sources.

Description

A small E. coli model, created from a number of sources.

Usage

ecoli_core

Format

A data frame with 95 rows and 7 columns:

abbreviation

an abbreviated reaction name, acts as the reaction id

lowbnd

lower bound on the reaction rate

uppbnd

upper bound on the reaction rate

obj_coef

identifies a reaction (or reactions) for which the maximum possible rate should be found

equation

reaction equation

officialName

full reaction name

geneAssociation

A boolean combination of genes which control the reaction

subsystem

an indicator of reaction function

Source

http://bigg.ucsd.edu, Reconstruction and Use of Microbial Metabolic Networks: the Core Escherichia coli Metabolic Model as an Educational Guide, A comprehensive genome-scale reconstruction of Escherichia coli metabolism–2011.

Parse a long format metabolic model to a glpk model

Description

This function is deprecated. ROI.plugin.glpk is recommended instead.

Usage

expanded_to_glpk(reactions_expanded)

Arguments

reactions_expanded

A list of data frames as output by reactiontbl_to_expanded

Details

This parses the long format produced by reactiontbl_to_expanded to a glpk model.

To install the Rglpk package in Linux, run sudo apt-get install libglpk-dev in a terminal, and then run install.packages('Rglpk') in R.

The reaction_table must have columns:

  • abbreviation,

  • equation,

  • uppbnd,

  • lowbnd, and

  • obj_coef.

Value

A list suitable for input to Rglpk

See Also

Other parsing_and_conversion: expanded_to_ROI(), expanded_to_gurobi(), reactiontbl_to_expanded(), reactiontbl_to_gurobi()

Parse a long format metabolic model to a Gurobi model

Description

This function is deprecated. github.com/Fl0Sch/ROI.plugin.gurobi is recommended instead.

Usage

expanded_to_gurobi(reactions_expanded)

Arguments

reactions_expanded

A list of data frames as output by expand_reactions

Details

Used as the second half of reactiontbl_to_gurobi, this parses the long format produced by reactiontbl_to_expanded to a Gurobi model

For installation instructions for Gurobi, refer to the Gurobi website: https://www.gurobi.com/.

The reaction_table must have columns:

  • abbreviation,

  • equation,

  • uppbnd,

  • lowbnd, and

  • obj_coef.

Value

A list suitable for input to Gurobi.

See Also

Other parsing_and_conversion: expanded_to_ROI(), expanded_to_glpk(), reactiontbl_to_expanded(), reactiontbl_to_gurobi()

Convert intermediate expanded format back to a reaction table

Description

Useful for saving a new or edited model

Usage

expanded_to_reactiontbl(expanded)

Arguments

expanded

A list of data frames:

  • rxns, which has one row per reaction,

  • mets, which has one row for each metabolite, and

  • stoich, which has one row for each time a metabolite appears in a reaction.

Value

A data frame describing the metabolic model.

Parse a long format metabolic model to an ROI model

Description

This parses the long format produced by reactiontbl_to_expanded to an ROI model.

Usage

expanded_to_ROI(reactions_expanded)

Arguments

reactions_expanded

A list of data frames as output by reactiontbl_to_expanded

Details

To solve models using ROI, you will need a solver plugin for ROI. Probably the easiest one to install is ROI.plugin.glpk. To install this in Linux, run sudo apt-get install libglpk-dev in a terminal, and then run install.packages('ROI.plugin.glpk') in R.

The reaction_table must have columns:

  • abbreviation,

  • equation,

  • uppbnd,

  • lowbnd, and

  • obj_coef.

Value

A list suitable for input to ROI.

See Also

Other parsing_and_conversion: expanded_to_glpk(), expanded_to_gurobi(), reactiontbl_to_expanded(), reactiontbl_to_gurobi()

Examples

## Not run: 
data(ecoli_core)
library(dplyr)
try(library(ROI.plugin.ecos)) # make a solver available to ROI

roi_model <- ecoli_core %>%
  reactiontbl_to_expanded %>%
  expanded_to_ROI
  
if(length(ROI::ROI_applicable_solvers(roi_model))>=1){
  roi_result <- ROI::ROI_solve(roi_model)
  
  ecoli_core_with_flux <- ecoli_core %>%
    mutate(flux = roi_result[['solution']])
}

## End(Not run)

fbar: Flux Balance Analysis in R with a tidy data approach

Description

fbar is a simple, easy to use Flux Balance Analysis package with a tidy data approach. Just data_frames and the occasional list, no new classes to learn. The focus is on simplicity and speed. Models are expected as a flat table, and results can be simply appended to the table. This makes this package very suitable for use in pipelines with pre- and post- processing of models and results, so that it works well as a backbone for customized methods. Loading, parsing and evaluating a model takes around 0.1s, which, together with the straightforward data structures used, makes this library very suitable for large parameter sweeps.

Details

For a list of functions in the package, see vignette('Introduction','fbar')

Given a metabolic model as a data frame, return a new data frame with fluxes and variability

Description

This function calculates fluxes folds times with shuffled versions of the metabolic model. This is designed to detect and quantify underdetermined fluxes.

Usage

find_flux_variability_df(reaction_table, folds = 10, do_minimization = TRUE)

Arguments

reaction_table

a data frame representing the metabolic model
folds

number of times to calculate fluxes
do_minimization

toggle to uniformly minimize all non-objective fluxes after finding the objective

Details

This function uses ROI, so to solve models, you will need a solver plugin for ROI. Probably the easiest one to install is ROI.plugin.glpk. To install this in Linux, run sudo apt-get install libglpk-dev in a terminal, and then run install.packages('ROI.plugin.glpk') in R.

Value

reaction_table with two added columns: sd (the standard deviation of fluxes found) and flux (a typical flux) from this distribution

Given a metabolic model as a data frame, return a new data frame with fluxes

Description

Given a metabolic model as a data frame, return a new data frame with fluxes

Usage

find_fluxes_df(reaction_table, do_minimization = FALSE)

Arguments

reaction_table

a data frame representing the metabolic model
do_minimization

toggle to uniformly minimize all non-objective fluxes after finding the objective

Details

This function uses ROI, so to solve models, you will need a solver plugin for ROI. Probably the easiest one to install is ROI.plugin.glpk. To install this in Linux, run sudo apt-get install libglpk-dev in a terminal, and then run install.packages('ROI.plugin.glpk') in R.

Value

The input data frame with a new numeric column, "flux".

See Also

find_fluxes_vector

Examples

## Not run: 
data(ecoli_core)
ecoli_core_with_flux <- find_fluxes_df(ecoli_core)

## End(Not run)

Apply gene expressions to reaction table

Description

A convenience function that uses gene_eval and a custom function to apply new upper and lower bounds.

Usage

gene_associate(
  reaction_table,
  gene_table,
  expression_flux_function = function(x) {     (1 + log(x)/stats::sd(x)^2)^sign(x - 1)
    }
)

Arguments

reaction_table

A data frame describing the metabolic model.
gene_table

A data frame showing gene presence
expression_flux_function

a function to convert from gene set expression to flux

Value

the reaction_table, with a new column, present, and altered upper and lower bounds

Warning

This function relies on gene_eval, which uses eval to evaluate gene expression sets. This gives flexibility, but means that malicious code in the gene_sets argument could get evaluated. gene_sets is evaluated in a restricted environment, but there might be a way around this, so you might want to check for anything suspicious in this argument manually. For more information, read the code.

See Also

gene_eval

Examples

data(iJO1366)
library(dplyr)

gene_table = tibble(name = iJO1366$geneAssociation %>%
stringr::str_split('and|or|\\s|\\(|\\)') %>%
  purrr::flatten_chr() %>%
  unique,
presence = 1) %>%
  filter(name != '', !is.na(name))

gene_associate(reaction_table = iJO1366 %>%
                 mutate(geneAssociation = geneAssociation %>%
                          stringr::str_replace_all('and', '&') %>%
                          stringr::str_replace_all('or', '|')
                 ),
               gene_table = gene_table
)

Function to estimate the expression levels of gene sets

Description

Function to estimate the expression levels of gene sets

Usage

gene_eval(gene_sets, genes, presences)

Arguments

gene_sets

A list of gene set strings: names of genes punctuated with &, | and brackets.
genes

A list of gene names
presences

A list of gene presences, the same length as genes

Value

a vector the same length as gene_sets, with the the calculated combined gene expression levels.

This function evaluates the gene sets in the context of the gene presences. It can take booleans, or numbers, in which case it associates & with finding the minimum, and | with finding the maximum.

Warning

This function uses eval to evaluate gene expression sets. This gives flexibility, but means that malicious code in the gene_sets argument could get evaluated. gene_sets is evaluated in a restricted environment, but there might be a way around this, so you might want to check for anything suspicious in this argument manually. For more information, read the code.

See Also

gene_associate

Download a model from a BiGG json file

Description

Download a model from a BiGG json file

Usage

get_BiGG(address)

Arguments

address

An address to download from

Value

A model in expanded format

A full size E. coli model.

Description

A full size E. coli model.

Usage

iJO1366

Format

A data frame with 2,583 rows and 10 columns:

abbreviation

an abbreviated reaction name, acts as the reaction id

lowbnd

lower bound on the reaction rate

uppbnd

upper bound on the reaction rate

obj_coef

identifies a reaction (or reactions) for which the maximum possible rate should be found

equation

reaction equation

officialName

full reaction name

geneAssociation

A boolean combination of genes which control the reaction

subsystem

an indicator of reaction function

Source

http://bigg.ucsd.edu, A comprehensive genome-scale reconstruction of Escherichia coli metabolism–2011.

A subset of exchange reactions annotated to indicate typical availability

Description

A subset of exchange reactions annotated to indicate typical availability

Usage

nutrient_types

Format

A data frame with 25 rows and 2 columns:

abbreviation

an exchange reaction id

nutrient_type

the nutrient availability, one of 'micro', 'macro' or 'substrate'

Internal function: Expand half reaction equations into a long form

Description

Internal function: Expand half reaction equations into a long form

Usage

parse_met_list(mets)

Arguments

mets

Character vector of halves of reaction equations.

Value

a date_frame with columns:

stoich

the stoichiometric coefficient

met

the metabolite

Parse a reaction table to an intermediate, long format

Description

The long format can also be suitable for manipulating equations.

Usage

reactiontbl_to_expanded(reaction_table, regex_arrow = "<?[-=]+>")

Arguments

reaction_table

A data frame describing the metabolic model.
regex_arrow

Regular expression for the arrow splitting sides of the reaction equation.

Details

The reaction_table must have columns:

  • abbreviation,

  • equation,

  • uppbnd,

  • lowbnd, and

  • obj_coef.

Value

A list of data frames:

  • rxns, which has one row per reaction,

  • mets, which has one row for each metabolite, and

  • stoich, which has one row for each time a metabolite appears in a reaction.

See Also

Other parsing_and_conversion: expanded_to_ROI(), expanded_to_glpk(), expanded_to_gurobi(), reactiontbl_to_gurobi()

Examples

## Not run: 
data(ecoli_core)
library(dplyr)
try(library(ROI.plugin.ecos)) # make a solver available to ROI

roi_model <- ecoli_core %>%
  reactiontbl_to_expanded %>%
  expanded_to_ROI
  
if(length(ROI::ROI_applicable_solvers(roi_model))>=1){
  roi_result <- ROI::ROI_solve(roi_model)
  
  ecoli_core_with_flux <- ecoli_core %>%
    mutate(flux = roi_result[['solution']])
}

## End(Not run)

Parse reaction table to Gurobi format

Description

This function is deprecated. github.com/Fl0Sch/ROI.plugin.gurobi is recommended instead.

Usage

reactiontbl_to_gurobi(reaction_table, regex_arrow = "<?[-=]+>")

Arguments

reaction_table

A data frame describing the metabolic model.
regex_arrow

Regular expression for the arrow splitting sides of the reaction equation.

Details

Parses a reaction table to give a list in Gurobi's input format. This function is a shorthand for reactiontbl_to_expanded followed by expanded_to_gurobi.

The reaction_table must have columns:

  • abbreviation,

  • equation,

  • uppbnd,

  • lowbnd, and

  • obj_coef.

Value

A list suitable for input to Gurobi.

See Also

Other parsing_and_conversion: expanded_to_ROI(), expanded_to_glpk(), expanded_to_gurobi(), reactiontbl_to_expanded()

Merge metabolite stub and compartment to form an id

Description

Merge metabolite stub and compartment to form an id

Usage

recompose_metabolites(
  expanded_metabolites,
  before_signifier = "_",
  after_signifier = ""
)

Arguments

expanded_metabolites

a metabolite table as created by decompose_metabolites
before_signifier

a string that is inserted before the compartment identifier
after_signifier

a string that is inserted after the compartment identifier

Value

A merged metabolite table with one column, met

Examples

data(ecoli_core)

mod <- reactiontbl_to_expanded(ecoli_core)

decompose_metabolites(mod$mets)

recompose_metabolites(decompose_metabolites(mod$mets))

Internal function: Splitting reaction equation into substrate and product

Description

Internal function: Splitting reaction equation into substrate and product

Usage

split_on_arrow(equations, regex_arrow = "<?[-=]+>")

Arguments

equations

Character vector of reaction equations.
regex_arrow

Regular expression for the arrow splitting sides of the reaction equation.

Value

a data_frame, with columns:

reversible

boolean, is reaction reversible

before

the left hand side of the reaction string

after

the right hand side of the reaction string

Validate an expanded model

Description

Validate an expanded model

Usage

validate_expanded(reactions_expanded)

Arguments

reactions_expanded

the expanded model to check

Value

TRUE