Package 'kinograte'

Combines standardized scores

Description

This function ranks combines standardized scores from each omic ranked dataset

Usage

combine_scores(df_rna = NULL, df_prot = NULL, df_kin = NULL, tf_kin = NULL)

Arguments

df_rna	dataframe with percentile ranking of RNA features
df_prot	dataframe with percentile ranking of protein features
df_kin	dataframe with percentile ranking of kinase features
tf_kin	dataframe with percentile ranking of transcription factor features

Value

dataframe with combined scores

Examples

TRUE

---

Integrate omic datasets using PCSF

Description

This function integrates omic datasets using prize-collecting Steiner forest (PCSF) algorithm

Usage

kinograte(
  df,
  ppi_network,
  n = 10,
  w = 10,
  r = 0.1,
  b = 2,
  mu = 0.005,
  cluster = TRUE,
  seed = NULL
)

Arguments

df	combined ranked omic datasets
ppi_network	dataframe of protein-protein interactions
n	An integer value to determine the number of runs with random noise added edge costs. A default value is 10.
w	A numeric value for tuning the number of trees in the output. A default value is 2.
r	A numeric value to determine additional random noise to edge costs. A random noise upto r percent of the edge cost is added to each edge. A default value is 0.1
b	A numeric value for tuning the node prizes. A default value is 1.
mu	A numeric value for a hub penalization. A default value is 0.0005.
cluster	set TRUE to cluster the network
seed	(optional) set seed number

Value

list(network, nodes, edges)

---

an example of Kinome data

Description

an example of Kinome data

Usage

kinomics_exmaple

Format

A data frame with 234 rows and 2 variables:

hgnc_symbol

Gene Symbols of kinases

score

normlaized score

---

Network pathway analysis

Description

This function performs pathway enrichment analysis on the intergated network

Usage

network_enrichment(network, ...)

Arguments

network	integrated network
...	arguments passed to PCSF::enrichment_analysis()

Value

df enriched terms

---

Ranks genes/proteins using a percentile ranking for a selected variable

Description

This function ranks genes or proteins using a percentile ranking for a selected variable (for example, fold change or pvalue)

Usage

percentile_rank(df, symbol, metric, desc = FALSE)

Arguments

df	dataframe that contains genes/proteins to rank (tidy format)
symbol	column name that contains the gene/protein symbols
metric	column name to be used as the metric to rank
desc	boolean, ranking in a descending or ascending order. Default = FALSE

Value

dataframe with percentile ranking

Examples

TRUE

---

an example of ppi network

Description

an example of ppi network

Usage

ppi_network_example

Format

A data frame with 175205 rows and 3 variables:

head

Protein 1

tail

Protein 2

cost

inverse degree of confidence

---

an example of proteomics data

Description

an example of proteomics data

Usage

proteomics_exmaple

Format

A data frame with 141 rows and 2 variables:

Gene.Symbol

Gene Symbols

LFC

log2 fold change

---

an example of RNA differential gene expression data

Description

an example of RNA differential gene expression data

Usage

rnaseq_example

Format

A data frame with 3207 rows and 3 variables:

Gene name

Gene Symbols

LFC

log2 fold change

P_Value

pvalue

---

Plot the normalized score

Description

This function plots the normalized score. Two options available: static or interactive plot

Usage

score_plot(
  df,
  prec_cutoff = 0.8,
  title = "Score Plot",
  subtitle = "",
  interactive = T
)

Arguments

df	dataframe that contains ranked genes/proteins
prec_cutoff	the percentile cutoff
title	plot title
subtitle	plot subtitle
interactive	boolean, option for an interactive plot. Default = TRUE

Value

dataframe of the top hits

---

Extracts top hits (genes/proteins) based on the normalized score

Description

This function extracts the top hits (genes/proteins) based on the normalized score which is the percentile rank using an adjustable cutoff

Usage

top_hits(df, prec_cutoff, omic_type)

Arguments

df	dataframe that contains ranked genes/proteins
prec_cutoff	the percentile cutoff
omic_type	name of omic dataset (eg. RNA, Protein, Kinase, ... etc)

Value

dataframe of the top hits

Examples

TRUE

---

Visualize integrated network

Description

This function visualizes the integrated results with an interactive network

Usage

visualize_network(
  nodes,
  edges,
  cluster_df = NULL,
  layout = "layout_with_fr",
  seed = 123,
  options_by = "group"
)

Arguments

nodes	network nodes
edges	network edges
cluster_df	(optional) network clusters dataframe generated by the kinograte function
layout	layout option from igraph. default = "layout_with_fr". See full list
seed	(optional) set seed
options_by	(optional) set dropdown menu, "group" or "cluster". Set NULL to remove dropdown menu

Value

visNetwork object

---