Package 'KINNET'

Title: Kinase INteraction NETwork Generation
Description: This package provides the functionality to process PamGene's PamChip Data Output and generate kinase interaction networks from that. This project uses a bayesian algorithm to generate bayesian networks for defining dependence relationships between peptide sequences in the PamChip data. It then uses a novel kinase assignment method to assign upstream kinases to each peptide which is then output as a graph.
Authors: Ali Sajid Imami [aut, cre] , Khaled Alganem [aut] , Justin Fortune Creeden [aut] , Alex Joyce [aut]
Maintainer: Ali Sajid Imami <[email protected]>
License: GPL (>= 3) | file LICENSE
Version: 0.4.0.9002
Built: 2024-06-29 04:45:56 UTC
Source: https://github.com/CogDisResLab/KINNET

Help Index

Assign kinases, given a network and a chip type

Description

Assign kinases, given a network and a chip type

Usage

assign_kinases(network, chiptype, identifier = "Gene_Symbol")

Arguments

network

A network output from bnlearn
chiptype

Either PTK or STK
identifier

The identifier to use in outputs. Can be either "Gene_Symbol" or "Kinase"

Value

A dataframe with upstream kinases assigned to the peptide

Examples

TRUE

Assign kinases, given a network and a chip type and additional essential kinases

Description

Assign kinases, given a network and a chip type and additional essential kinases

Usage

assign_kinases_guided(
  network,
  chiptype,
  identifier = "Gene_Symbol",
  guided = NULL
)

Arguments

network

A network output from bnlearn
chiptype

Either PTK or STK
identifier

The identifier to use in outputs. Can be either "Gene_Symbol" or "Kinase"
guided

A vector of Kinases or Gene_Symbols that must be included in the network. The vector must be aligned with what was specified in _identifier_

Value

A dataframe with upstream kinases assigned to the peptide

Examples

TRUE

Generate Candidate Kinases Based On Links

Description

Generate Candidate Kinases Based On Links

Usage

candidate_kinases(peptide, arcs, assigned_kinases)

Arguments

peptide

Peptide ID
arcs

The arcs in the network
assigned_kinases

The candidate kinases

Value

common kinases

Examples

TRUE

Compare two kinased graphhs

Description

This functions takes two given graphs and compares them to see the changes from one to the other

Usage

compare_kinased_graphs(
  reference,
  comparison,
  ref_name = "Reference",
  comp_name = "Comparison",
  render = FALSE
)

Arguments

reference

The reference network output from assign_kinases()
comparison

The comparison network output from assign_kinases()
ref_name

Name for the reference network
comp_name

Name for the comparison network
render

logical. Whether a graph should be rendered or not.

Value

A graph object

Examples

TRUE

Equalize the nodesets of two kinased graphs

Description

Equalize the nodesets of two kinased graphs

Usage

equalize_kinase_graphs(reference, comparison)

Arguments

reference

a reference result from assign_kinases()
comparison

a comparison result from assign_kinases()

Value

A list with two elements, reference and comparison, that have the same nodesets

Examples

TRUE

Return a list of significant peptides

Description

Return a list of significant peptides

Usage

filter_peptides(chipdata, threshold = 0.75)

Arguments

chipdata

an object of class PamchipSTK or PamchipPTK
threshold

a lower cutoff for significance

Value

a list of significant peptides for each class

Examples

TRUE

Do a standardized fit of expression data from a single peptide's activity

Description

Do a standardized fit of expression data from a single peptide's activity

Usage

fit_standardized(expr)

Arguments

expr

a dataframe containing the activity data of only one peptide

Value

a list of three items std_10, std_50 and std_200, of standardized linear coefficients

Examples

TRUE

Generate Intersections between kinases

Description

Generate Intersections between kinases

Usage

get_intersections(row, column, assigned_kinases)

Arguments

row

row peptide
column

column peptide
assigned_kinases

Kinases assigned

Value

common kinases beween the two groups

Examples

TRUE

Calculate the Hamming Distance between two kinased graphs

Description

Calculate the Hamming Distance between two kinased graphs

Usage

kinnet_hamming(reference, comparison)

Arguments

reference

a reference result from assign_kinases()
comparison

a comparison result from assign_kinases()

Value

A positive integer

Examples

TRUE

Calculate Normalized Hamming Distance

Description

Calculate Normalized Hamming Distance

Usage

kinnet_normalized_hamming(reference, comparison)

Arguments

reference

a reference result from assign_kinases()
comparison

a reference result from assign_kinases()

Value

A positive integer

Examples

TRUE

Calculate Normalized Structural Hamming Distance

Description

Calculate Normalized Structural Hamming Distance

Usage

kinnet_normalized_shd(reference, comparison)

Arguments

reference

a reference result from assign_kinases()
comparison

a comparison result from assign_kinases()

Value

A positive integer

Examples

TRUE

Calculate the Structural Hamming Distance between two kinased graphs

Description

Calculate the Structural Hamming Distance between two kinased graphs

Usage

kinnet_shd(reference, comparison)

Arguments

reference

a reference result from assign_kinases()
comparison

a comparison result from assign_kinases()

Value

A positive integer

Examples

TRUE

Generate a bayes net model

Description

Generate a bayes net model

Usage

make_model(expression, iterations = 200, threshold = NULL, cluster = NULL)

Arguments

expression

tbl_df. A tibble with the activity data from the kinome chip.
iterations

numeric. Number of iterations to run the mode.
threshold

numeric. Threshold to use for averaging the network
cluster

cluster. (Optional) a cluster from the package parallel

Value

A list with the strength network dataframe, an averaged network and the threshold used to generate that averaged network.

Examples

TRUE

Process a file into a usable structure

Description

Process a file into a usable structure

Usage

PamchipData_PTK(dataset)

Arguments

dataset

character. Path to a file that holds the output of BioNavigator

Value

An object of class PamchipData-PTK

Examples

TRUE

Process a file into a usable structure

Description

Process a file into a usable structure

Usage

PamchipData_STK(dataset)

Arguments

dataset

character. Path to a file that holds the output of BioNavigator

Value

An object of class PamchipData-STK

Examples

TRUE

The Pamchip Data Superclass

Description

The Pamchip Data Superclass

Value

an object of class PamchipData

Slots

chip_type

character. A string

Examples

TRUE

A representation of the PamChip PTK Data

Description

A representation of the PamChip PTK Data

Value

An object of class PamchipData-PTK

Slots

BioNavigatorVersion

character. A string indicating the version of BioNavigator that generated the dataset

ImageAnalysisDate

character. The date the analysis was conducted on.

PamGridVersion

character. PamGrid version the chip was run on.

QuantitationType

character. The kind of qunatitation analysis performed.

SampleData

tbl_df. A tibble with the observed activity on each peptide

SampleCharacteristics

tbl_df. A tibble with the characteristics of each sample

RefData

tbl_df.

PeptideIDs

character.

ProcessedData

tbl_df.

DataProcessDate

character. The date when the data was processed

Examples

TRUE

A representation of the PamChip STK Data

Description

A representation of the PamChip STK Data

Value

An object of class PamchipData-STK

Slots

BioNavigatorVersion

character. A string indicating the version of BioNavigator that generated the dataset

ImageAnalysisDate

character. The date the analysis was conducted on.

PamGridVersion

character. PamGrid version the chip was run on.

QuantitationType

character. The kind of qunatitation analysis performed.

SampleData

tbl_df. A tibble with the observed activity on each peptide

SampleCharacteristics

tbl_df. A tibble with the characteristics of each sample

RefData

tbl_df.

PositiveControlData

tbl_df.

PeptideIDs

character.

DataProcessDate

character. The date when the data was processed

Examples

TRUE

PTK Peptide to Kinase Probability Matrix for Gene Identifiers

Description

A dataframe with the Bayesian posteriors of finding a given peptide/kinase pair

Usage

ptk_probability_matrix_gene

Format

A dataframe with 991 rows and 3 columns

peptide

The peptide ID

kinase

Gene Symbol of the kinase

posterior

Posterior probability of the pair

PTK Peptide to Kinase Probability Matrix for Kinase Identifiers

Description

A dataframe with the Bayesian posteriors of finding a given peptide/kinase pair

Usage

ptk_probability_matrix_kinase

Format

A dataframe with 991 rows and 3 columns

peptide

The peptide ID

kinase

Gene Symbol of the kinase

posterior

Posterior probability of the pair

Generate a kianse graph

Description

Generate a kianse graph

Usage

render_kinased_graph(analysis_result, title, render = FALSE)

Arguments

analysis_result

Object output from assign_kinases()
title

Title of the graph
render

logical. Whether a graph should be rendered or not.

Value

a graph object

Examples

TRUE

Generate a reduced kianse graph

Description

Generate a reduced kianse graph

Usage

render_reduced_kinased_graph(analysis_result, title, render = FALSE)

Arguments

analysis_result

Object output from assign_kinases()
title

Title of the graph
render

logical. Whether a graph should be rendered or not.

Value

a graph object

Examples

TRUE

Add a node safely to a bn object

Description

This function takes a bn object and a node and adds it if it's not already in the nodeset.

Usage

safely_add_node(net, node)

Arguments

net

A bn object
node

A node label

Value

A bn object with the node added

Examples

TRUE

STK Data Accessor Functions

Description

These functions provide a variety of data setters and getter for the Pamchip objects.

Usage

pheno_data(chipdata, ...)

## S4 method for signature ''PamchipData-STK''
pheno_data(chipdata)

exp_data(chipdata, ...)

## S4 method for signature ''PamchipData-STK''
exp_data(chipdata)

classes(chipdata, ...)

## S4 method for signature ''PamchipData-STK''
classes(chipdata)

peptides(chipdata, ...)

## S4 method for signature ''PamchipData-STK''
peptides(chipdata)

Arguments

chipdata

an object of class PamchipData-STK or PamchipData-PTK
...

Currently unused

Details

These functions allow you to get and set the slots of the object.

  • processed_data accesses the processed and transformed data

  • pheno_data gives the sample characteristics

  • exp_data access the actual intensity values

  • classes gives the unique classes in the chip

  • peptides gives the reference list of peptides on the chip

Value

The requested object

STK Peptide to Kinase Probability Matrix for Gene Identifiers

Description

A dataframe with the Bayesian posteriors of finding a given peptide/kinase pair

Usage

stk_probability_matrix_gene

Format

A dataframe with 10428 rows and 3 columns

peptide

The peptide ID

kinase

Gene Symbol of the kinase

posterior

Posterior probability of the pair

STK Peptide to Kinase Probability Matrix for Kinase Identifiers

Description

A dataframe with the Bayesian posteriors of finding a given peptide/kinase pair

Usage

stk_probability_matrix_kinase

Format

A dataframe with 10428 rows and 3 columns

peptide

The peptide ID

kinase

Gene Symbol of the kinase

posterior

Posterior probability of the pair

Subset The Kinome Data

Description

Subset the Kinome data to a given list of peptides and conditions

Usage

subset_data(chipdata, peptides, class)

Arguments

chipdata

Pamchip-PTK. A Pamchip-PTK Object with all the data available
peptides

character. A vector of peptides of interest
class

character. A specification of the sample class you want to filter to

Value

A tibble with the filtered and asinh transformed data

Examples

TRUE

Calculated Updated Probabilities of each peptide/kinase pair

Description

Calculated Updated Probabilities of each peptide/kinase pair

Usage

update_probability_matrix(
  chiptype,
  assignment_df,
  identifier = "Gene_Symbol",
  guided = NULL
)

Arguments

chiptype

character. Either "STK" or "PTK"
assignment_df

tbl_df. A tibble with the potential kianse assignments
identifier

The identifier to use in outputs. Can be either "Gene_Symbol" or "Kinase"
guided

A vector of Kinases or Gene_Symbols that must be included in the network. The vector must be aligned with what was specified in _identifier_

Value

an updated dataframe with the probabilities

Examples

TRUE