Package 'BioPathNet'

Construct a BPNList object

Description

Construct a BPNList object

Usage

BPNList(input, gsea, enrichr, ilincs, leading, revigo, integrated)

Arguments

input	tbl_df A tibble with the differentially expressed genes
gsea	GSEAResult An object containing the GSEA results
enrichr	EnrichRResult An object containing the EnrichR results
ilincs	iLINCSResult An object containing the iLINCS results
leading	LEResult An object containing the Leading Edge Analysis results
revigo	RevigoResult An object containing the Revigo results
integrated	IntegratedResult An object containing the Integrated results

Value

A BPNList object

Examples

TRUE

---

BPNList-class: The BioPathNet Core Class

Description

This class takes care of the entire analysis infrastructure of the BioPathNet analysis. This class is created with inputting a list of differentially expressed genes and then stores the subsequently generated results.

Value

An object of class BPNList

Slots

input

tbl_df. A tibble with Two columns of gene names and logfc values and optionally a p-value column

gsea

GSEAResult. An instance of GSEAResult-class class storing the results GSEA Analysis

enrichr

EnrichRResult. An instance of EnrichRResult-class class storing the results EnrichR Analysis

ilincs

iLINCSResult. An instance of iLINCSResult-class class storing the results iLINCS Analysis

leading

LEResult. An instance of LEResult-class class storing the results Leading Edge Analysis

revigo

RevigoResult. An instance of RevigoResult-class class storing the results Revigo Analysis

integrated

IntegratedResult. An instance of IntegratedResult-class class storing the results after integrating the three components

Examples

TRUE

---

Perform the EnrichR Analysis

Description

This function takes in a BPNList object and returns a BPNList object with the enrichr slot updated with process EnrichR Results

Usage

do_enrichr_pod(bpn, alpha = 0.05, lower = NULL, upper = NULL, useFDR = TRUE)

Arguments

bpn	BPNList An object of class BPNList created from prepare_data
alpha	numeric The Alpha value for statistical significance. Defaults to 0.05.
lower	numeric The cutoff for down-regulated genes. If not specified, it takes the bottom 10% of the
upper	numeric The cutoff for up-regulated genes. If not specified, it takes the top 10% of the dataset
useFDR	logical Whether to filter by adjusted p-value

Details

This function takes in a BPNList object and returns a BPNList object with the enrichr slot updated with process EnrichR Results.

Value

An object of class BPNList with its enrichr slot populated with the results

Examples

TRUE

---

Perform the Geneset Enrichment Analysis

Description

This function takes a BPNList object and performs a Geneset Enrichment Analysis and returns a BPNList object with the results of the GSEA

Usage

do_gsea_pod(
  bpn,
  species = "hsapiens",
  gmtfile = NULL,
  lower = NULL,
  upper = NULL,
  alpha = 0.05,
  minSize = 15,
  maxSize = 500,
  rankWithSignificance = FALSE,
  useFDR = TRUE
)

Arguments

bpn	BPNList An object of class BPNList created from prepare_data
species	character One of the species for which we provide current GMT pathways. Currently the valid species are hsapiens, mmusculus and rnorvegicus. Cannot be specified along with gmtfile
gmtfile	character A full path to a GMT File you would like to use. Cannot be specified along with species
lower	numeric The cutoff for down-regulated genes. If not specified, it takes the bottom 10% of the dataset
upper	numeric The cutoff for up-regulated genes. If not specified, it takes the top 10% of the dataset
alpha	numeric The Alpha value for statistical significance. Defaults to 0.05.
minSize	numeric The minimum number of genes that should be in a pathway for it to be included in the analysis
maxSize	numeric The maximum number of genes that should be in a pathway for it to be included in the analysis
rankWithSignificance	logical Whether to rank genes using p-values
useFDR	logical Whether to filter by adjusted p-value

Details

This function takes a BPNList object and performs a Geneset Enrichment Analysis and returns a BPNList object with the results of the GSEA

Value

An object of class BPNList with its gsea slot populated with the results

Examples

TRUE

---

Perform Leading Edge Gene Analysis

Description

This method takes in a bpn object and performs a leading edge analysis to identify the genes that are driving the majority of pathways.

Usage

do_leading_pod(bpn)

Arguments

bpn	An object of class BPNList. Must have the gsea analysis completed beforehand.

Value

An object of class BPNList with its leading slot populated with the results

Examples

TRUE

---

Construct an EnrichRResult object

Description

Construct an EnrichRResult object

Usage

EnrichRResult(
  up_results,
  down_results,
  upreg,
  downreg,
  alpha,
  upper,
  lower,
  dbs,
  useFDR
)

Arguments

up_results	tbl_df A tibble of enrichment results from the upregulated genes
down_results	tbl_df A tibble of enrichment results from the upregulated genes
upreg	tbl_df A tibble of up-regulated genes
downreg	tbl_df A tibble of down-regulated genes
alpha	numeric Alpha level of significance
upper	numeric Upper threshold for up-regulated genes
lower	numeric Lower threshold for down-regulated genes
dbs	character a vector of the databases used for the enrichment analysis
useFDR	logical Whether to filter by adjusted p-value

Value

an object of class EnrichRResult

Examples

TRUE

---

EnrichRResult-class: Class storing EnrichR Results

Description

This class stores the input parameters and results of the Gene Set Enrichment Analysis.

Value

an object of class EnrichRResult

Slots

alpha

numeric. The Alpha threshold for significance

threshold_up

numeric. The logfc threshold for up-regulated genes

threshold_down

numeric. The logfc threshold for down-regulated genes

upregulated_genes

tbl_df. The up-regulated genes from the input DEG tibble

downregulated_genes

tbl_df. The down-regulated genes from the input DEG tibble

dbs_used

character. A vector of the databases used from enrichR

up_enrichr

tbl_df. Enriched pathways in up-regulated genes

down_enrichr

tbl_df. Enriched pathways in down-regulated genes

sig_up_enrichr

tbl_df. Significant enriched pathways in up-regulated genes

sig_down_enrichr

tbl_df. Significant enriched pathways in down-regulated genes

num_upreg

numeric. Number of up-regulated genes

num_downreg

numeric. Number of down-regulated genes

num_up_enrichr

numeric. Number of enriched pathways in up-regulated genes

num_down_enrichr

numeric. Number of enriched pathways in down-regulated genes

num_sig_up_enrichr

numeric. Number of significant enriched pathways in up-regulated genes

num_sig_down_enrichr

numeric. Number of significant enriched pathways in down-regulated genes

empty

logical. A simple check for whether or not the object is empty

Examples

TRUE

---

Perform Revigo enrichment analysis

Description

Perform Revigo enrichment analysis

Usage

get_revigo_output(input_data)

Arguments

input_data

A dataframe containing GO IDs and associated p-values

Value

A dataframe containing the Revigo Enrichment analysis

Examples

TRUE

---

Construct a GSEAResult Object

Description

Construct a GSEAResult Object

Usage

GSEAResult(results, pathways, lower, upper, alpha, upreg, downreg, useFDR)

Arguments

results	tbl_df A tibble with the results from fgsea
pathways	list A list of vectors with gene sets
lower	numeric Lower threshold for down-regulated genes
upper	numeric Upper threshold for up-regulated genes
alpha	numeric Alpha level of significance
upreg	tbl_df A tibble of up-regulated genes
downreg	tbl_df A tibble of down-regulated genes
useFDR	logical Whether to filter by adjusted p-value

Value

an object of class GSEAResult

Examples

TRUE

---

GSEAResult-class: Class storing GSEA Results

Description

This class stores the input parameters and results of the Gene Set Enrichment Analysis.

Value

an object of class GSEAResult

Slots

alpha

numeric. The Alpha threshold for significance

threshold_up

numeric. The logfc threshold for up-regulated genes

threshold_down

numeric. The logfc threshold for down-regulated genes

upregulated_genes

tbl_df. The up-regulated genes from the input DEG tibble

pathways

tbl_df. The pathways we used, either built-in or user-supplied

downregulated_genes

tbl_df. The down-regulated genes from the input DEG tibble

pos_enriched

tbl_df. The positively enriched pathways

neg_enriched

tbl_df. The negatively enriched pathways

sig_pos_enriched

tbl_df. Significant positively enriched pathways

sig_neg_enriched

tbl_df. Significant positively enriched pathways

num_upreg

numeric. Number of up-regulated genes

num_downreg

numeric. Number of down-regulated genes

num_tested

numeric. Number of pathways tested

num_pos_enriched

numeric. Number of positively enriched pathways

num_neg_enriched

numeric. Number of negatively enriched pathways

num_sig_pos_enriched

numeric. Number of significant positively enriched pathways

num_sig_neg_enriched

numeric. Number of significant negatively enriched pathways

empty

logical. A simple check for whether or not the object is empty

Examples

TRUE

---

List of pathways and associated genes in homo sapiens

Description

The processed form of the October 2020 Pathway annotation containing every pathway annotated with the associated genes in humans. This uses the Symbol annotation from BaderLab.

Usage

hsapiens

Format

A list

Source

http://download.baderlab.org/EM_Genesets/October_01_2020/Human/symbol/Human_GO_AllPathways_with_GO_iea_October_01_2020_symbol.gmt

---

iLINCSResult-class: Class storing iLINCS Results

Description

This class stores the result of the results from iLINCS

Value

an object of class iLINCSResult

Slots

threshold_up

numeric. LFC threshold for up-regulated genes

threshold_down

numeric. LFC threshold for down-regulated genes

threshold_pval

numeric. P Value threshold for genes.

threshold_similarity

numeric. Similarity threshold

l1000_subset

tbl_df. Subset of L1000 genes in the dataset

upregulated_genes

tbl_df. L1000 genes up-regulatedd in dataset

downregulated_genes

tbl_df. L1000 genes down-regulated in dataset

ilincs_query_signature

tbl_df. Complete iLINCS Query signature

all_perturbagens

tbl_df. Complete list returned from iLINCS of perturbagens

filtered_perturbagens

tbl_df. Filtered list of perturbagens by the similarity threshold

num_genes_l1000

numeric. Number of L1000 genes in dataset

num_genes_upregulated

numeric. Number of up-regulated L1000 genes in dataset

num_genes_downregulated

numeric. Number of down-regulated L1000 genes in dataset

num_all_perturbagens

numeric. Number of all perturbagens returned by iLINCS

num_filtered_perturbagens

numeric. Number of filtered perturbagens returned by iLINCS

empty

logical. A simple check for whether or not the object is empty

Examples

TRUE

---

IntegratedResult-class: Class containing Integrated results

Description

IntegratedResult-class: Class containing Integrated results

Value

and object of class IntegratedResults

Slots

placeholder

numeric.

empty

logical. A simple check for whether or not the object is empty

Examples

TRUE

---

Extract Leading Edge Genes from GSEA Results

Description

Extract Leading Edge Genes from GSEA Results

Usage

leading_edge(gsea, direction)

Arguments

gsea	an object of class GSEAResult
direction	one of "up" or "down"

Value

A tibble with the leading edge genes and associated pathways

Examples

TRUE

---

Construct an LEResult object

Description

Construct an LEResult object

Usage

LEResult(leading_up, leading_down)

Arguments

leading_up	tbl_df. A dataframe with the results of all the leading edge genes from upregulated genes
leading_down	tbl_df. A dataframe with the results of all the leading edge genes from downregulated genes

Value

An object of class LEResult

Examples

TRUE

---

LEResult-class: Class containing Leading Edge Analysis results

Description

LEResult-class: Class containing Leading Edge Analysis results

Value

an object of class LEResult

Slots

leading_up

tbl_df. A tibble with the results of LE analysis for the upregulated pathways

leading_down

tbl_df. A tibble with the results of LE analysis for the downregulated pathways

count_leading_up

tbl_df. A tibble with the counts of LE genes for the upregulated pathways

count_leading_down

tbl_df. A tibble with the counts of LE genes for the downregulated pathways

num_leading_up

numeric. Number of LE genes for the upregulated pathways

num_leading_down

numeric. Number of LE genes for the downregulated pathways

empty

logical. A simple check for whether or not the object is empty

Examples

TRUE

---

Load Pathways data

Description

Load Pathways data

Usage

load_pathways(species)

Arguments

species

The species. Can be hsapiens, mmusculus or rnorvegicus

Value

The loaded pathways

importFrom utils data

Examples

TRUE

---

List of pathways and associated genes in mus musculus

Description

The processed form of the October 2020 Pathway annotation containing every pathway annotated with the associated genes in mice. This uses the Symbol annotation from BaderLab.

Usage

mmusculus

Format

A list

Source

http://download.baderlab.org/EM_Genesets/October_01_2020/Mouse/symbol/Mouse_GO_AllPathways_with_GO_iea_October_01_2020_symbol.gmt

---

Prepare the data for downstream analysis

Description

This function takes vectors of gene names, log Fold-change values and optionally p-values and formats them into a tibble for downstream analysis.

Usage

prepare_data(genes, logfc, pvalues = NULL)

Arguments

genes	a character vector of gene names
logfc	a numeric vector of log fold-change values
pvalues	(optional) a numeric vector of p-values

Details

The function returns an object of class BPNList that will update as the analysis proceeds

Value

An object of class BPNList with the following slot set:

input

Examples

TRUE

---

RevigoResult-class: Class containing results from Revigo

Description

RevigoResult-class: Class containing results from Revigo

Value

and object of class RevigoResult

Slots

placeholder

numeric.

empty

logical. A simple check for whether or not the object is empty

Examples

TRUE

---

List of pathways and associated genes in rattus norvegicus

Description

The processed form of the October 2020 Pathway annotation containing every pathway annotated with the associated genes in rats. This uses the Symbol annotation from BaderLab.

Usage

rnorvegicus

Format

A list

Source

http://download.baderlab.org/EM_Genesets/October_01_2020/MRat/symbol/Rat_GO_AllPathways_with_GO_iea_October_01_2020_symbol.gmt

---