Package 'bioCancer'

Title: Interactive Multi-Omics Cancers Data Visualization and Analysis
Description: This package is a Shiny App to visualize and analyse interactively Multi-Assays of Cancer Genomic Data.
Authors: Karim Mezhoud [aut, cre]
Maintainer: Karim Mezhoud <[email protected]>
License: AGPL-3 | file LICENSE
Version: 1.35.0
Built: 2024-11-29 04:17:02 UTC
Source: https://github.com/bioc/bioCancer

Help Index

Private Escape string

Description

Does not escape strings, but raises an error if any character expect normal letters and underscores are found in the string.

Usage

.dbEscapeString(str, raise.error = TRUE)

Arguments

str

String to test
raise.error

Logical, whether to raise an error or not.

Value

Invisible logical

Gets the table name from the INPARANOID style genus names.

Description

Gets the table name from the INPARANOID style genus names.

Usage

.getTableName(genus)

Arguments

genus

5 character INPARANOID genus name, such as "BOSTA", "HOMSA" or "MUSMU".

Value

Table name for genus.

Author(s)

Stefan McKinnon Edwards [email protected]

References

https://www.bioconductor.org/packages/release/bioc/html/AnnotationDbi.html

Secret function that does the magic for pickRefSeq.

Description

Do not use it, use pickRefSeq!

Usage

.pickRef(l, priorities, reduce = c("all", "first", "last"))

Arguments

l

List.
priorities

How to prioritize.
reduce

How to reduce.

Value

List.

Note

Hey, you found a secret function! Keep it that way!

Author(s)

Stefan McKinnon Edwards [email protected]

See Also

pickRefSeq

Annotation translation functions

Description

Package: AnnotationFuncs
Type: Package
Version: 1.3.0
Date: 2011-06-10
License: GPL-2
LazyLoad: yes

Details

Functions for handling translations between different identifieres using the Biocore Data Team data-packages (e.g. org.Bt.eg.db). Primary functions are translate for translating and getOrthologs for efficient lookup of homologes using the Inparanoid databases. Other functions include functions for selecting Refseqs or Gene Ontologies (GO).

Author(s)

Stefan McKinnon Edwards [email protected]

References

https://www.iysik.com/index.php?page=annotation-functions

See Also

translate, getOrthologs

Examples

library(org.Bt.eg.db)
gene.symbols <- c('DRBP1','SERPINA1','FAKE','BLABLA')
# Find entrez identifiers of these genes.
eg <- translate(gene.symbols, org.Bt.egSYMBOL2EG)
# Note that not all symbols were translated.

# Go directly to Refseq identifiers.
refseq <- translate(gene.symbols, from=org.Bt.egSYMBOL2EG, to=org.Bt.egREFSEQ)
# Pick the proteins:
 pickRefSeq(refseq, priorities=c('NP','XP'), reduce='all')

Attribute Color to Gene

Description

Attribute Color to Gene

Usage

attriColorGene(df)

Arguments

df

data frame with mRNA or CNA or mutation frequency or methylation (numeric). Without sampleID column.

Value

A list colors for every gene

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

Attribute Color to Value

Description

Attribute Color to Value

Usage

attriColorValue(Value, df, colors=c(a,b,c),feet)

Arguments

Value

integer
df

data frame with numeric values
colors

a vector of 5 colors
feet

the interval between two successive colors in the palette (0.1)

Value

Hex Color Code

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

Attribute color to a vector of numeric values

Description

Attribute color to a vector of numeric values

Usage

attriColorVector(Value, vector, colors=c(a,b,c),feet)

Arguments

Value

numeric
vector

A vector of numeric data
colors

3 colors
feet

An interval between two numeric value needed to change the color

Value

A vetor of colors

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

Attribute shape to nodes

Description

Attribute shape to nodes

Usage

attriShape2Gene(gene, genelist)

Arguments

gene

Gene symbol
genelist

Gene list

Value

A character "BRCA1[shape = 'circle', "

Examples

how <- "runManually"
## Not run: 
GeneList <- whichGeneList("73")
attriShape2Gene("P53", GeneList)
attriShape2Gene("GML",GeneList)

## End(Not run)

Attributes shape to Nodes

Description

Attributes shape to Nodes

Usage

attriShape2Node(gene, genelist)

Arguments

gene

symbol "TP53"
genelist

a vector of gene symbol

Value

A data frame with egdes attributes

Examples

GeneList <- c("DKK3" , "NBN"  , "MYO6" , "TP53" , "PML"  , "IFI16" ,"BRCA1")
NodeShape <- attriShape2Gene("DKK3", GeneList)

Launch bioCancer with default browser

Description

The Main function to run bioCancer App

Usage

bioCancer()

Value

web page of bioCancer Shiny App

Examples

ShinyApp <-  1
## Not run: 
bioCancer()

## End(Not run)

CGDS connect object to cBioPortal

Description

Creates a CGDS connection object from a CGDS endpoint URL. This object must be passed on to the methods which query the server.

Usage

CGDS(url,verbose=FALSE,ploterrormsg='',token=NULL)

Arguments

url

A CGDS URL (required).
verbose

A boolean variable specifying verbose output (default FALSE)
ploterrormsg

An optional message to display in plots if an error occurs (default ”)
token

An optional 'Authorization: Bearer' token to connect to cBioPortal instances that require authentication (default NULL)

Check wich Cases and genetic profiles are available for selected study

Description

Check wich Cases and genetic profiles are available for selected study

Usage

checkDimensions(StudyID)

Arguments

StudyID

Study reference using cBioPortal index

Value

A data frame with two column (Cases, Genetic profiles). Every row has a dimension (CNA, mRNA...). The data frame is filled with yes/no response.

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

This is an htmlwidgets-based visualization tool for hierarchical data. It is zoomable, meaning that you can interact with the hierarchy and zoom in/out accordingly.

Description

This is an htmlwidgets-based visualization tool for hierarchical data. It is zoomable, meaning that you can interact with the hierarchy and zoom in/out accordingly.

Usage

coffeewheel(treeData, width=600, height=600, main="", partitionAttribute="value")

Arguments

treeData

A hierarchical tree data as in example
width

600
height

600
main

Title
partitionAttribute

"value"

Value

A circular layout with genetic profile.

Examples

How <- "runManually"
## Not run: 
 coffeewheel(treeData = sampleWheelData)
 
## End(Not run)

Widget output function for use in Shiny

Description

Widget output function for use in Shiny

Usage

coffeewheelOutput(outputId, width=700, height=700)

Arguments

outputId

id
width

700
height

700

Value

A circular layout with genetic profile in Shiny App.

Examples

How <- "runManually"
## Not run: 
coffeewheel(treeData = sampleWheelData)

## End(Not run)

Display dataframe in table using DT package

Description

Display dataframe in table using DT package

Usage

displayTable(df)

Arguments

df

a dataframe

Value

A table

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

get Edges dataframe for Gene/Disease association from geNetClassifier

Description

get Edges dataframe for Gene/Disease association from geNetClassifier

Usage

Edges_Diseases_obj(genesclassdetails)

Arguments

genesclassdetails

a dataframe from geNetClassifier

Value

A data frame with egdes attributes

Examples

GenesClassDetails <- structure(list(Genes = c("FANCF", "MLH1", "MSH2", "ATR", "PARP1",
"CHEK2", "RAD51"), ranking = c(1L, 1L, 1L, 2L, 3L, 1L, 2L), class = c("brca_tcga",
"gbm_tcga", "lihc_tcga", "lihc_tcga", "lihc_tcga", "lusc_tcga",
"lusc_tcga"), postProb = c(1, 0.99, 1, 0.99, 0.99, 1,
0.98), exprsMeanDiff = c(180, 256, -373, -268,
-1482, 258, 143), exprsUpDw = c("UP", "UP", "DOWN",
"DOWN", "DOWN", "UP", "UP")), .Names = c("Genes", "ranking",
"class", "postProb", "exprsMeanDiff", "exprsUpDw"),
class = "data.frame", row.names = c(NA,-7L))

Ed_Diseases_obj <- Edges_Diseases_obj(genesclassdetails=GenesClassDetails)

Default dataset of bioCancer

Description

Default dataset of bioCancer

Usage

epiGenomics

Format

An object of class data.frame with 48 rows and 7 columns.

Author(s)

Karim Mezhoud [email protected]

Check if PhantomJS is installed. Similar to webshot

Description

Check if PhantomJS is installed. Similar to webshot

Usage

findPhantom()

Value

Logic object

Examples

How <- "runManually"
## Not run: 
findPhantom()

## End(Not run)

Returns GO evidence codes.

Description

Returns GO evidence codes.

Usage

getEvidenceCodes()

Value

Matrix of two columns, first column with codes, second column with description of codes.

Author(s)

Stefan McKinnon Edwards [email protected]

References

?org.Bt.egGO

See Also

pickGO

Examples

getEvidenceCodes()

get mutation frequency

Description

get mutation frequency

Usage

getFreqMutData(list, geneListLabel)

Arguments

list

a list of data frame with mutation data. Each data frame is for one study
geneListLabel

file name of geneList examples: "73"

Value

a data frame with mutation frequency. gene is in rows and study is in column

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

get genes classification

Description

get genes classification

Usage

getGenesClassification(checked_Studies, GeneList,
 samplesize, threshold, listGenProfs, listCases)

Arguments

checked_Studies

checked studies
GeneList

gene list
samplesize

sample size
threshold

p-value threshold
listGenProfs

list of genetic profiles
listCases

list of cases

Value

A table with genes classed by study

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

get list of cases of each selected study in Classifier panel

Description

get list of cases of each selected study in Classifier panel

Usage

getList_Cases(checked_Studies)

Arguments

checked_Studies

checked studies

Value

A list of cases

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

get list of genetic profiles of each selected study in Classifier panel

Description

get list of genetic profiles of each selected study in Classifier panel

Usage

getList_GenProfs(checked_Studies)

Arguments

checked_Studies

checked studies

Value

A list of genetics profiles

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

get list of data frame with profiles data (CNA,mRNA, Methylation, Mutation...)

Description

get list of data frame with profiles data (CNA,mRNA, Methylation, Mutation...)

Usage

getListProfData(checked_Studies, geneListLabel)

Arguments

checked_Studies

checked studies in corresponding panel (input$StudiesIDCircos, input$StudiesIDReactome).
geneListLabel

The label of GeneList. There are three cases: "Genes" user gene list, "Reactome_GeneList" GeneList plus genes from reactomeFI "file name" from Examples

Value

A LIST of profiles data (CNA, mRNA, Methylation, Mutation, miRNA, RPPA). Each dimension content a list of studies.

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

Performs quicker lookup for orthologs in homologe data packages

Description

Using the INPARANOID data packages such as hom.Hs.inp.db is very, very slow and can take up to 11 min (on this particular developers workstation). This function introduces a new method that can do it in just 20 seconds (on the developers workstation). In addition, it includes options for translating between different identifers both before and after the mapping.

Usage

getOrthologs(
  values,
  mapping,
  genus,
  threshold = 1,
  pre.from = NULL,
  pre.to = NULL,
  post.from = NULL,
  post.to = NULL,
  ...
)

Arguments

values

Vector, coerced to character vector, of values needed mapping by homology.
mapping

Homology mapping object, such as hom.Hs.inpBOSTA or revmap(hom.Hs.inpBOSTA).
genus

Character vector. 5 character INPARANOID style genus name of the mapping object, e.g. 'BOSTA' for both hom.Hs.inpBOSTA and revmap(hom.Hs.inpBOSTA).
threshold

Numeric value between 0 and 1. Only clustered homologues with a parwise score above the threshold is included. The native implementation has this set to 1.
pre.from

Mapping object if values needs translation before mapping. E.g. values are entrez and hom.Hs.inpBOSTA requires ENSEMBLPROT, hom.Hs.inpAPIME requires Refseq (?). Arguments from and to are just like in translate.
pre.to

Second part of translation before mapping.
post.from

Translate the result from homology mapping to a desired id; just like in translate.
post.to

Second part of translation after mapping.
...

Additional arguments sent to translate.

Value

List. Names of list corresponds to values, except those that could not be mapped nor translated. Entries are character vectors.

Author(s)

Stefan McKinnon Edwards [email protected]

References

?hom.Hs.inp.db - https://inparanoidb.sbc.su.se/

Berglund, A.C., Sjolund, E., Ostlund, G., Sonnhammer, E.L.L. (2008) InParanoid 6: eukaryotic ortholog clusters with inparalogs Nucleic Acids Res. 36:D263–266

O'Brien, K.P., Maido, R., Sonnhammer, E.L.L (2005) Inparanoid: A Comprehensive Database of Eukaryotic Orthologs NAR 33:D476–D480

Remm, M., Storm, C.E.V, Sonnhammer, E.L.L (2001) Automatic clustering of orthologs and in-paralogs from pairwise species comparisons J. Mol. Biol. 314:1041–1052

See Also

translate, .getTableName, mapLists

Examples

tmp <-1

search and get genetic profiles (CNA,mRNA, Methylation, Mutation...)

Description

search and get genetic profiles (CNA,mRNA, Methylation, Mutation...)

Usage

getProfData(study,genProf, listGenProf, GeneList, Mut)

Arguments

study

Study ID
genProf

Genetic Profile id (cancer_study_id_[mutations, cna, methylation, mrna ]).
listGenProf

A list of Genetic Profiles for one study.
GeneList

A list of genes
Mut

Condition to set if the genetic profile is mutation or not (0,1)

Details

See https://github.com/kmezhoud/bioCancer/wiki

Value

A data frame with Genetic profile

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

get samples size of sequensed genes

Description

get samples size of sequensed genes

Usage

getSequensed_SampleSize(StudiesID)

Arguments

StudiesID

Studies ID as a vector

Value

dataframe with sample size for each selected study.

Examples

## Not run: 
 sampleSize <- getSequensed_SampleSize(input$StudiesIDCircos)

## End(Not run)

Replaces contents of list A with elements of list B

Description

Combines two lists, A and B, such that names(A) are preserved, mapping to the values of B, using names(B) as look up. Ie. replaces values in A with values in B, using names(B) as look up for values in A. Once more? See examples. NB! None-mapped entries are returned as NA, but can be removed using removeNAs.

Usage

mapLists(A, B, removeNAs = TRUE)

Arguments

A

List, elements are coerced to character for mapping to B.
B

List.
removeNAs

Boolean, whether to remove the NAs that occur because an element was not found in B.

Value

List.

Author(s)

Stefan McKinnon Edwards [email protected]

See Also

removeNAs

Examples

A <- list('a1'='alpha','a2'='beta','a3'=c('gamma','delta'))
B <- list('alpha'='b1', 'gamma'=c('b2', 'b3'), 'delta'='b4')
mapLists(A, B)

Circular plot of hierarchital data of genetic profile.

Description

Circular plot of hierarchital data of genetic profile.

Usage

metabologram(treeData,width=600,height=600,main="",showLegend=FALSE,
                     legendBreaks=NULL,
                     legendColors=NULL,
                      fontSize=12,
                     legendText="Legend")

Arguments

treeData

A hierarchical tree data as in example
width

600
height

600
main

Title
showLegend

FALSE
legendBreaks

NULL
legendColors

NULL
fontSize

12
legendText

Legend

Value

A circular layout with genetic profile.

See Also

https://github.com/armish/metabologram

Examples

How <- "runManually"
## Not run: 
 metabologram(treeData = sampleWheelData, width=600,
 height=600, main="title", showLegend = TRUE, fontSize = 10,
 legendBreaks=c("NA","Min","Negative", "0", "Positive", "Max"),
 legendColors=c("black","blue","cyan","white","yellow","red") ,
 legendText="Legend")
 
## End(Not run)

Widget output function for use in Shiny

Description

Widget output function for use in Shiny

Usage

metabologramOutput(outputId, width = 600, height = 500)

Arguments

outputId

id
width

600
height

600

Value

A circular plot with genetic profile in Shiny App.

Examples

## Not run: 
library(bioCancer)
bioCancer::metabologram(treeData = sampleMetabologramData)

## End(Not run)

Atribute mutation frequency to nodes

Description

Atribute mutation frequency to nodes

Usage

Mutation_obj(list,FreqMutThreshold, geneListLabel)

Arguments

list

A list of data frame with mutation data. Each data frame to study
FreqMutThreshold

threshold Rate of cases (patients) having mutation (0-1).
geneListLabel

file name of geneList examples: "73"

Value

A dat frame with mutation frequency. Ech column corresponds to a study.

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

Attributes size to Nodes depending on number of interaction

Description

Attributes size to Nodes depending on number of interaction

Usage

Node_df_FreqIn(genelist, freqIn)

Arguments

genelist

a vector of genes
freqIn

dataframe with Node interaction frequencies

Value

A data frame with nodes size attributes

Examples

Node_df_FreqIn
## Not run: 
r_data <- new.env()
r_data[["FreqIn"]] <- structure(list(Genes = c("ATM", "ATR", "BRCA1", "BRCA2", "CHEK1",
"CHEK2", "FANCF", "MDC1", "RAD51"), FreqSum = c(0.04, 0.05, 0.05,
 0.03, 0.05, 0.04, 0.03, 0.03, 0.02)), .Names = c("Genes", "FreqSum"),
 class = "data.frame", row.names = c(NA, -9L))
GeneList <- whichGeneList("DNA_damage_Response")
node_df <- Node_df_FreqIn(GeneList, r_data$FreqIn)

## End(Not run)

Attributes color and shape to Nodes of Diseases

Description

Attributes color and shape to Nodes of Diseases

Usage

Node_Diseases_obj(genesclassdetails)

Arguments

genesclassdetails

a dataframe from geNetClassifier function

Value

A data frame with nodes Shapes and colors

Examples

GenesClassDetails <- structure(list(Genes = c("FANCF", "MLH1", "MSH2", "ATR", "PARP1",
"CHEK2", "RAD51"), ranking = c(1L, 1L, 1L, 2L, 3L, 1L, 2L), class = c("brca_tcga",
"gbm_tcga", "lihc_tcga", "lihc_tcga", "lihc_tcga", "lusc_tcga",
"lusc_tcga"), postProb = c(1, 0.99, 1, 0.99, 0.99, 1,
0.98), exprsMeanDiff = c(180, 256, -373, -268,
-1482, 258, 143), exprsUpDw = c("UP", "UP", "DOWN",
"DOWN", "DOWN", "UP", "UP")), .Names = c("Genes", "ranking",
"class", "postProb", "exprsMeanDiff", "exprsUpDw"),
class = "data.frame", row.names = c(NA,-7L))
Node_Diseases_df <- Node_Diseases_obj(genesclassdetails= GenesClassDetails)

Attribute CNA data to node border

Description

Attribute CNA data to node border

Usage

Node_obj_CNA_ProfData(list)

Arguments

list

A list of data frame with CNA data. Each data frame corresponds to a study.

Value

A data frame with node border attributes

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

Attribute interaction frequency to node size

Description

Attribute interaction frequency to node size

Usage

Node_obj_FreqIn(geneList)

Arguments

geneList

A list of gene symbol

Value

A data frame with node attributes

Examples

r_data <- new.env()
r_data[["FreqIn"]] <- structure(list(Genes = c("ATM", "ATR", "BRCA1", "BRCA2", "CHEK1",
"CHEK2", "FANCF", "MDC1", "RAD51"), FreqSum = c(0.04, 0.05, 0.05,
 0.03, 0.05, 0.04, 0.03, 0.03, 0.02)), .Names = c("Genes", "FreqSum"),
 class = "data.frame", row.names = c(NA, -9L))
 ## Not run: 
GeneList <- whichGeneList("DNA_damage_Response")
nodeObj <- Node_obj_FreqIn(GeneList)

## End(Not run)

Attribute gene Methylation to Nodes

Description

Attribute gene Methylation to Nodes

Usage

Node_obj_Met_ProfData(list, type, threshold)

Arguments

list

a list of data frame with methylation data
type

HM450 or HM27
threshold

the Rate cases (patients) that have a silencing genes by methylation

Value

a data frame with node shape attributes

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

Atrribute genes expression to color nodes

Description

Atrribute genes expression to color nodes

Usage

Node_obj_mRNA_Classifier(geneList,genesclassdetails)

Arguments

geneList

A gene list.
genesclassdetails

A dataframe with genes classes and genes expression.

Value

A data frame with node color attributes

Examples

r_data <- new.env()
input <- NULL

r_data[["FreqIn"]] <- structure(list(Genes = c("ATM", "ATR", "BRCA1", "BRCA2", "CHEK1",
"CHEK2", "FANCF", "MDC1", "RAD51"), FreqSum = c(0.04, 0.05, 0.05,
 0.03, 0.05, 0.04, 0.03, 0.03, 0.02)), .Names = c("Genes", "FreqSum"),
 class = "data.frame", row.names = c(NA, -9L))

GenesClassDetails <- structure(list(Genes = c("FANCF", "MLH1", "MSH2", "ATR", "PARP1",
"CHEK2", "RAD51"), ranking = c(1L, 1L, 1L, 2L, 3L, 1L, 2L), class = c("brca_tcga",
"gbm_tcga", "lihc_tcga", "lihc_tcga", "lihc_tcga", "lusc_tcga",
"lusc_tcga"), postProb = c(1, 0.99, 1, 0.99, 0.99, 1,
0.98), exprsMeanDiff = c(180, 256, -373, -268,
-1482, 258, 143), exprsUpDw = c("UP", "UP", "DOWN",
"DOWN", "DOWN", "UP", "UP")), .Names = c("Genes", "ranking",
"class", "postProb", "exprsMeanDiff", "exprsUpDw"),
class = "data.frame", row.names = c(NA,-7L))
## Not run: 
GeneList <- whichGeneList("DNA_damage_Response")
nodeObj <- Node_obj_mRNA_Classifier(GeneList, GenesClassDetails)

## End(Not run)

Cleans up result from org.Xx.egGO and returns specific GO identifiers

Description

Cleans up result from org.Xx.egGO and returns GO identifier for either biological process (BP), cellular component (CC), or molecular function (MF). Can be used on list of GOs from translate, or a single list of GOs from an annotation package. May reduce list, if the (sub)list does not contain the chosen class!

Usage

pickGO(l, evidence = NA, category = NA)

Arguments

l

Character vector, or list of GO identifiers.
evidence

Character vector, filters on which kind of evidence to return; for a larger list see getEvidenceCodes. \* Evidence codes may be: c('IMP','IGI','IPI','ISS','IDA','IEP','IEA','TAS','NAS','ND','IC'). \* Leave as NA to ignore filtering on this part.
category

Character vector, filters on which ontology to return: biological process (BP), cellular component (CC), or molecular function (MF). \* Leave as NA to ignore filtering on this part.

Value

List with only the picked elements.

Author(s)

Stefan McKinnon Edwards [email protected]

See Also

pickRefSeq, getEvidenceCodes, translate

Examples

library(org.Bt.eg.db)
genes <- c(280705, 280706, 100327208)
translate(genes, org.Bt.egSYMBOL)

symbols <- c("SERPINA1","KERA","CD5")
refseq <- translate(symbols, from=org.Bt.egSYMBOL2EG, to=org.Bt.egREFSEQ)
# Pick the proteins:
pickRefSeq(refseq, priorities=c('NP','XP'), reduce='all')

# If you wanted do do some further mapping on the result from
# translate, simply use lapply.

library(GO.db)
GO <- translate(genes, org.Bt.egGO)
# Get all biological processes:
## Not run: 
pickGO(GO, category='BP')
 # $`280705`
 # [1] "GO:0006826" "GO:0006879"
 # $`280706`
# [1] "GO:0006590" "GO:0007165" "GO:0042446"
# Get all ontologies with experimental evidence:
pickGO(GO, evidence=c('IMP','IGI','IPI','ISS','IDA','IEP','IEA'))
 # $`280705`
 # [1] "GO:0006826" "GO:0006879" "GO:0005615" "GO:0008199"
 # $`280706`
 # [1] "GO:0006590" "GO:0007165" "GO:0042446" "GO:0005615" "GO:0005179" "GO:0042393"

## End(Not run)

Picks a prioritised RefSeq identifier from a list of identifiers

Description

When translating to RefSeq, typically multiple identifiers are returned, referring to different types of products, such as genomic molecule, mature mRNA or the protein, and they can be predicted, properties that can be read from the prefix (https://www.ncbi.nlm.nih.gov/refseq/). E.g. "XM_" is predicted mRNA and "NP_" is a protein. Run ?org.Bt.egREFSEQ.

Usage

pickRefSeq(
  l,
  priorities = c("NP", "XP", "NM", "XM"),
  reduce = c("all", "first", "last")
)

Arguments

l

Vector or list of RefSeqs accessions to pick from. If list given, applies the prioritation to each element in the list.
priorities

Character vector of prioritised prefixes to pick by. Eg. c("NP","NM") returns RefSeqs starting 'NP', and if none found, those starting 'NM'. If no RefSeqs are found according to the priorities, Null is returned, unless the last element in priorities is '*'. Uses grepl, so see these for pattern matching. Default: c('NP','XP','NM','XM')
reduce

Reducing method, either return all annotations (one-to-many relation) or the first or last found annotation. The reducing step is applied after translating to the goal: all: returns all annotations first or last: choose first or last of arbitrarily ordered list.

Value

If vector given, returns vector. If list given, returns list without element where nothing could be picked.

Author(s)

Stefan McKinnon Edwards [email protected]

Examples

library(org.Bt.eg.db)
symbols <- c("SERPINA1","KERA","CD5")
refseq <- translate(symbols, from=org.Bt.egSYMBOL2EG, to=org.Bt.egREFSEQ)
mRNA <- pickRefSeq(refseq, priorities=c('NM','XM'))
proteins <- pickRefSeq(refseq, priorities=c('NP','XP'))

Removes entries equal NA from list or vector

Description

Removes entries equal NA, but not mixed entries containing, amongst others, NA. Good for use after mapLists that might return entries equal NA.

Usage

removeNAs(l)

Arguments

l

Vector or list.

Author(s)

Stefan McKinnon Edwards [email protected]

Examples

removeNAs(list('a'=NA, 'b'=c(NA, 'B'), 'c'='C'))

Widget render function for use in Shiny

Description

Widget render function for use in Shiny

Usage

renderCoffeewheel(expr,env =  parent.frame(),  quoted = FALSE)

Arguments

expr

id
env

parent.frame()
quoted

FALSE

Value

A circular layout with genetic profile in Shiny App.

Examples

How <- "runManually"
## Not run: 
coffeewheel(treeData = sampleWheelData)

## End(Not run)

Widget render function for use in Shiny

Description

Widget render function for use in Shiny

Usage

renderMetabologram(expr, env= parent.frame(),  quoted = FALSE)

Arguments

expr

expression
env

parent.frame()
quoted

FALSE

Value

A circular plot with genetic profile in Shiny App.

Examples

## Not run: 
library(bioCancer)
bioCancer::metabologram(treeData = sampleMetabologramData)

## End(Not run)

Restructure the list of color attributed to the genes in every dimenssion for every studies

Description

Restructure the list of color attributed to the genes in every dimenssion for every studies

Usage

reStrColorGene(df)

Arguments

df

data frame with colors attributed to the genes

Value

Hierarchical color attribute: gene > color

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

Restructure the list of color attributed to the genes in every study for every dimensions

Description

Restructure the list of color attributed to the genes in every study for every dimensions

Usage

reStrDimension(LIST)

Arguments

LIST

list of hierarchical dimensions

Value

Hierarchical structure of: Study > dimensions > gene > color

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

Restructure the list of color attributed to the genes in every disease

Description

Restructure the list of color attributed to the genes in every disease

Usage

reStrDisease(List)

Arguments

List

of data frame with color attributes

Value

Hierarchy of dimensions in the same study: dimensions > gene > color

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

Return message when the filter formula is not correct (mRNA > 500)

Description

Return message when the filter formula is not correct (mRNA > 500)

Usage

returnTextAreaInput(inputId,
                          label= NULL,
                          rows = 2,
                         placeholder = NULL,
                         resize= "vertical",
                         value = "")

Arguments

inputId

The ID of the object
label

Text describes the box area
rows

Number of rows
placeholder

Error message if needed
resize

orientation of text
value

default text in the area box

Value

text message

Examples

ShinyApp <-  1
## Not run: 
returnTextAreaInput(inputId = "data-filter",
                    label = "Error message",
                    rows =  2,
                    placeholder = "Provide a filter (e.g., Genes == 'ATM') and press return",
                    resize = "vertical",
                    value="")

## End(Not run)

get object for grViz. Link Studies to genes

Description

get object for grViz. Link Studies to genes

Usage

Studies_obj(df)

Arguments

df

data frame with gene classes

Value

grViz object. a data frame with Study attributes

Examples

Studies_obj(data.frame("col1", "col2", "col3", "col4", "col5", "col6"))
## Not run: 
Genes ranking     class postProb exprsMeanDiff exprsUpDw
1 FANCF       1 brca_tcga  1.00000      179.9226        UP
2  MLH1       1  gbm_tcga  0.99703      256.3173        UP

## End(Not run)

A function to change the Original checkbox of rshiny into a nice true/false or on/off switch button No javascript involved. Only CSS code.

Description

To be used with CSS script 'button.css' stored in a 'www' folder in your Shiny app folder

Usage

switchButton(inputId, label = NULL, value = FALSE, col = "GB", type = "TF")

Arguments

inputId

The input slot that will be used to access the value.
label

Display label for the control, or NULL for no label.
value

Initial value (TRUE or FALSE).
col

Color set of the switch button. Choose between "GB" (Grey-Blue) and "RG" (Red-Green)
type

Text type of the button. Choose between "TF" (TRUE - FALSE), "OO" (ON - OFF) or leave empty for no text.

S3 method to test cBioPortal connection

Description

S3 method to test cBioPortal connection

Usage

## S3 method for class 'CGDS'
test(x, ...)

Arguments

x

connection object
...

not used

Translate between different identifiers

Description

Function for translating from one annotation to another, eg. from RefSeq to Ensemble. This function takes a vector of annotation values and translates first to the primary annotation in the Biocore Data Team package (ie. entrez gene identifier for org.Bt.eg.db) and then to the desired product, while removing non-translated annotations and optionally reducing the result so there is only a one-to-one relation.

Usage

translate(
  values,
  from,
  to = NULL,
  reduce = c("all", "first", "last"),
  return.list = TRUE,
  remove.missing = TRUE,
  simplify = FALSE,
  ...
)

Arguments

values

Vector of annotations that needs translation. Coerced to character vector.
from

Type of annotation values are given in. NB! take care in the orientation of the package, ie. if you have RefSeq annotations, use org.Bt.egREFSEQ2EG or (in some cases) revmap(org.Bt.egREFSEQ).
to

Desired goal, eg. org.Bt.egENSEMBLPROT. If NULL (default), goal if the packages primary annotation (eg. entrez gene for org.Bt.eg.db). Throws a warning if the organisms in from and to are not the same.
reduce

Reducing method, either return all annotations (one-to-many relation) or the first or last found annotation. The reducing step is applied after translating to the goal: all: returns all annotations first or last: choose first or last of arbitrarily ordered list.
return.list

Logical, when TRUE, returns the translation as a list where names
remove.missing

Logical, whether to remove non-translated values, defaults TRUE.
simplify

Logical, unlists the result. Defaults to FALSE. Usefull when using translate in a lapply or sapply.
...

Additional arguments sent to pickGO if from returns GO set.

Details

If you want to do some further mapping on the result, you will have to use either unlist og lapply, where the first returns all the end-products of the first mapping, returning a new list, and the latter produces a list-within-list.

If from returns GO identifiers (e.g. from = org.Bt.egGO), then the returned resultset is more complex and consists of several layers of lists instead of the usual list of character vectors. If to has also been specified, the GO IDs must be extracted (internally) and you have the option of filtering for evidence and category at this point. See pickGO.

Value

List; names of elements are values and the elements are the translated elements, or NULL if not translatable with remove.missing = TRUE.

Note

Requires user to deliver the annotation packages such as org.Bt.egREFSEQ.

Author(s)

Stefan McKinnon Edwards [email protected]

See Also

pickRefSeq, pickGO

Examples

library(org.Bt.eg.db)
genes <- c(280705, 280706, 100327208)
translate(genes, org.Bt.egSYMBOL)

symbols <- c("SERPINA1","KERA","CD5")
refseq <- translate(symbols, from=org.Bt.egSYMBOL2EG, to=org.Bt.egREFSEQ)
# Pick the proteins:
pickRefSeq(refseq, priorities=c('NP','XP'), reduce='all')

# If you wanted do do some further mapping on the result from
# translate, simply use lapply.

library(GO.db)
GO <- translate(genes, org.Bt.egGO)

Unify row names in data frame with the same order of gene list.

Description

Unify row names in data frame with the same order of gene list.

Usage

UnifyRowNames(x,geneList)

Arguments

x

data frame with gene symbol in the row name
geneList

a gene list

Value

a data frame having the gene in row name ordered as in gene list.

Examples

cgds <- cBioPortal(
hostname = "www.cbioportal.org",
protocol = "https",
api = "/api/v2/api-docs"
)
## Not run: 
getDataByGenes( api =  cgds,
studyId = "gbm_tcga_pub",
genes = c("NF1", "TP53", "ABL1"),
by = "hugoGeneSymbol",
molecularProfileIds = "gbm_tcga_pub_mrna"
)

## End(Not run)

Example of Copy Number Alteration (CNA) dataset

Description

Example of Copy Number Alteration (CNA) dataset

Usage

user_CNA

Format

An object of class data.frame with 579 rows and 13 columns.

Author(s)

Karim Mezhoud [email protected]

Example of Methylation HM27 dataset

Description

Example of Methylation HM27 dataset

Usage

user_MetHM27

Format

An object of class data.frame with 600 rows and 13 columns.

Author(s)

Karim Mezhoud [email protected]

Example of Methylation HM450 dataset

Description

Example of Methylation HM450 dataset

Usage

user_MetHM450

Format

An object of class data.frame with 10 rows and 13 columns.

Author(s)

Karim Mezhoud [email protected]

Example of mRNA expression dataset

Description

Example of mRNA expression dataset

Usage

user_mRNA

Format

An object of class data.frame with 307 rows and 13 columns.

Author(s)

Karim Mezhoud [email protected]

Example of Mutation dataset

Description

Example of Mutation dataset

Usage

user_Mut

Format

An object of class data.frame with 37 rows and 23 columns.

Author(s)

Karim Mezhoud [email protected]

Verify which gene list is selected

Description

Verify which gene list is selected

Usage

whichGeneList(geneListLabel)

Arguments

geneListLabel

The label of GeneList. There are three cases: "Genes" user gene list, "Reactome_GeneList" GeneList plus genes from reactomeFI "file name" from Examples

Value

Gene List label

Examples

How <- "runManually"
## Not run: 
whichGeneList("102")

## End(Not run)

Capture html output widget as .png in R

Description

Capture html output widget as .png in R

Usage

widgetThumbnail(p, thumbName, width = 1024, height = 1024)

Arguments

p

is the html widget
thumbName

is the name of the new png file
width

1024
height

1024

Value

3 files .html, .js and .png

Examples

How <- "runManually"
## Not run: 
# Load package
library(networkD3)
library(htmlwidgets)
# Create fake data
src <- c("A", "A", "A", "A", "B", "B", "C", "C", "D")
target <- c("B", "C", "D", "J", "E", "F", "G", "H", "I")
networkData <- data.frame(src, target)
# Plot
plot = simpleNetwork(networkData)
# Save html as png
widgetThumbnail(p = plot, thumbName = "plot", width = 1024, height = 1024)

## End(Not run)