Package 'rcellminer'

Title: rcellminer: Molecular Profiles, Drug Response, and Chemical Structures for the NCI-60 Cell Lines
Description: The NCI-60 cancer cell line panel has been used over the course of several decades as an anti-cancer drug screen. This panel was developed as part of the Developmental Therapeutics Program (DTP, http://dtp.nci.nih.gov/) of the U.S. National Cancer Institute (NCI). Thousands of compounds have been tested on the NCI-60, which have been extensively characterized by many platforms for gene and protein expression, copy number, mutation, and others (Reinhold, et al., 2012). The purpose of the CellMiner project (http://discover.nci.nih.gov/ cellminer) has been to integrate data from multiple platforms used to analyze the NCI-60 and to provide a powerful suite of tools for exploration of NCI-60 data.
Authors: Augustin Luna, Vinodh Rajapakse, Fabricio Sousa
Maintainer: Augustin Luna <[email protected]>, Vinodh Rajapakse <[email protected]>, Fathi Elloumi <[email protected]>
License: LGPL-3 + file LICENSE
Version: 2.27.0
Built: 2024-07-18 06:01:22 UTC
Source: https://github.com/bioc/rcellminer

Help Index

Display citation message

Description

Display citation message

Usage

.onAttach(libname, pkgname)

Arguments

libname

a character string giving the library directory where the package defining the namespace was found.
pkgname

a character string giving the name of the package.

Make sure that rcellminerData is loaded

Description

Make sure that rcellminerData is loaded

Usage

.onLoad(libname, pkgname)

Arguments

libname

a character string giving the library directory where the package defining the namespace was found.
pkgname

a character string giving the name of the package.

Returns an indexed eSet object from a MolData object eSet list.

Description

Returns an indexed eSet object from a MolData object eSet list.

Usage

## S4 method for signature 'MolData'
x[[i]]

Arguments

x

A MolData object.
i

Index or named item in MolData object eSet list.

Value

An indexed eSet object from a MolData object eSet list.

Assigns an eSet object to a specified position in a MolData object eSet list.

Description

Assigns an eSet object to a specified position in a MolData object eSet list.

Usage

## S4 replacement method for signature 'MolData'
x[[i]] <- value

Arguments

x

A MolData object.
i

Index or named item in MolData object eSet list.
value

An eSet object to be assigned.

Value

An eSet object to a specified position in a MolData object eSet list.

CellMiner Version

Description

CellMiner Version

Details

The version of CellMiner used

Author(s)

Vinodh Rajapakse vinodh.rajapakse AT nih.gov

References

http://discover.nci.nih.gov/cellminer

Calculate cross-correlations with between rows of input matrices

Description

Calculate cross-correlations with between rows of input matrices

Usage

crossCors(X, Y = NULL, method = "pearson")

Arguments

X

a matrix or data.frame
Y

a matrix or data.frame
method

a string specifying the type of correlation, chosen from pearson (default) or spearman.

Value

a list containing matrices of pairwise correlations and their p-values between rows of the input matrices or dataframes.

Author(s)

Sudhir Varma, NCI-LMP, with input checks, support for Spearman's correlation added by VNR.

Examples

drugActData <- exprs(getAct(rcellminerData::drugData))
crossCors(drugActData[c("94600"), ], drugActData[c("727625", "670655"), ])
crossCors(drugActData[c("94600"), ], drugActData[c("727625", "670655"), ], method="spearman")

Calculate Spearman's correlations with between rows of input matrices

Description

Calculate Spearman's correlations with between rows of input matrices

Usage

crossCorsSpearman(X, Y = NULL)

Arguments

X

a matrix or data.frame
Y

a matrix or data.frame

Value

a list containing matrices of pairwise Spearman's correlations and their p-values between rows of the input matrices or dataframes.

Examples

## Not run: 
crossCorsSpearman(drugActData[c("94600"), ], drugActData[c("727625", "670655"), ])

## End(Not run)

A data frame with descriptive information for all compound mechanism of action (MOA) abbreviations used in CellMiner.

Description

A data frame with descriptive information for all compound mechanism of action (MOA) abbreviations used in CellMiner.

Returns a DrugData object.

Description

Returns a DrugData object.

Usage

DrugData(act, repeatAct, sampleData, ...)

Arguments

act

An eSet object containing drug activity data across a set of biological samples.
repeatAct

An eSet object containing repeat drug activity experiment data with respect to the same samples associated with act.
sampleData

A MIAxE object capturing sample and other data set information.
...

Other possible parameters.

Value

A DrugData object.

An S4 class to represent drug activity and related data recorded for a set of biological samples.

Description

An S4 class to represent drug activity and related data recorded for a set of biological samples.

Arguments

...

Other possible parameters.

Slots

act

An eSet object containing drug activity data across a set of biological samples.

repeatAct

An eSet object containing repeat drug activity experiment data with respect to the same samples associated with act.

sampleData

A MIAxE object capturing sample and other data set information.

Returns a DrugData object.

Description

Returns a DrugData object.

Usage

## S4 method for signature 'eSet,eSet,MIAxE'
DrugData(act, repeatAct, sampleData, ...)

Arguments

act

An eSet object containing drug activity data across a set of biological samples.
repeatAct

An eSet object containing repeat drug activity experiment data with respect to the same samples associated with act.
sampleData

A MIAxE object capturing sample and other data set information.
...

Other possible parameters.

Value

A DrugData object.

CellMiner Drug Response Values

Description

CellMiner Drug Response Values

Details

A list containing response values and annotations:

  • act Z-scores of the averaged negative log GI (growth inhibition) 50 values across repeats for the NCI-60; assay described here: http://dtp.nci.nih.gov/branches/btb/ivclsp.html

  • annot

    • id Dataset identifier; NOTE: DO NOT use this column; the NSC is the primary drug identifier

    • nsc National Service Center identifier; the primary drug identifier

    • name Compound name

    • brand_name Brand name for the compound, if sold commericially

    • formula Compound chemical formula

    • testing_status Information on whether it is known if the compound is FDA approved or undergoing testing in clinical trials

    • source TODO

    • smiles Compound chemical structure as a SMILES string

    • weight Compound chemical weight in g/mol

    • mechanism Pharmacological mechanism of action

    • confidential_flag A flag to indicate if compound information is public

    • total_probes TODO

    • total_good_probes TODO

    • low_correlations TODO

    • failure_reason TODO

    • cas CAS Registry Number; NOTE: Due to data restrictions PubChem IDs are the preferred mapping ID to other datasets

    • pubchem_id PubChem ID

Author(s)

Vinodh Rajapakse vinodh.rajapakse AT nih.gov

References

http://discover.nci.nih.gov/cellminer/loadDownload.do

NCI60 Molecular Data

Description

Z-scores of values for a variety of assays conducted on the NCI-60 to facilitate comparison. Z-scores calculated over the 60 cell lines for the given feature.

Details

A list containing various assay values:

  • cop Copy number values; Described in Pubmed ID: 24670534

  • exp Expression values; Obtained from "RNA: 5 Platform Gene Transcript" http://discover.nci.nih.gov/cellminer/loadDownload.do; Missing values imputed using the R package "impute"

  • mut Mutation values; Deleterious mutations obtained from TODO

  • mir MicroRNA values; Obtained from "RNA: Agilent Human microRNA (V2)" http://discover.nci.nih.gov/cellminer/loadDownload.do

  • pro Reverse protein lysate array values; Obtain from "Protein: Lysate Array" http://discover.nci.nih.gov/cellminer/loadDownload.do

  • mda NCI-60 metadata.

    • CNV_GAIN Proportion of genome copy number gains; Described in Pubmed ID: 24670534

    • CNV_LOSS Proportion of genome copy number losses; Described in Pubmed ID: 24670534

    • CNV_TOTAL Sum of CNV_GAIN and CNV_LOSS

    • P53_BIN Binary TP53 profile curated by William Reinhold

    • MSI_OGAN_BIN Binary microsatellite instability (MSI) profile curated by Ogan Abaan using COSMIC data; Obtained from Supplementary Table 1 - Ogan Whole Exome Sequencing (WES) paper in Cancer Res.

    • EPITHELIAL Epithelial by tissue of origin - pattern extracted from the CellMiner cell line metadata http://discover.nci.nih.gov/cellminer/celllineMetadata.do

    • EPITHELIAL_KURT Kurt Kohn curation for epithelial-like cell lines based on molecular parameters described in Pubmed ID: 24940735

    • DELETERIOUS Total deleterious variants from WES dataset; Fabricio Sousa curation

    • MISSENSE Total missense variants from WES dataset; Fabricio Sousa curation

    • SILENT Total silent variants from WES dataset; Fabricio Sousa curation

    • TOTAL_AA Total amino acid changing variants from WES dataset; Fabricio Sousa curation

    • CELL-CELL Cell-to-cell adhesion curated by William Reinhold

    • DOUBLINGTIME The doubling time pattern was extracted from the CellMiner cell line metadata http://discover.nci.nih.gov/cellminer/celllineMetadata.do

Author(s)

Vinodh Rajapakse vinodh.rajapakse AT nih.gov

References

http://discover.nci.nih.gov/cellminer

Molecular Fingerprint List

Description

Molecular Fingerprint List

Author(s)

Augustin Luna augustin AT mail.nih.gov

References

http://discover.nci.nih.gov/cellminer

Returns an eSet object with drug activity data.

Description

Returns an eSet object with drug activity data.

Usage

getAct(object, ...)

Arguments

object

Object for which drug activity data is to be returned.
...

Other possible parameters.

Value

An eSet object with drug activity data.

Returns an eSet object with drug activity data.

Description

Returns an eSet object with drug activity data.

Usage

## S4 method for signature 'DrugData'
getAct(object)

Arguments

object

DrugData object for which drug activity data is to be returned.

Value

An eSet object with drug activity data.

Returns a table of activity range statistics for a set of compounds.

Description

Returns a table of activity range statistics for a set of compounds.

Usage

getActivityRangeStats(
  nscSet,
  concFormat = "NegLogGI50M",
  onlyCellMinerExps = TRUE
)

Arguments

nscSet

a character vector specifying NSC identifier(s) for compound(s) of interest.
concFormat

a string selected from "NegLogGI50M" or "IC50MicroM". "NegLogGI50M" specifies activities as the negative log of the 50 inhibitory concentration (molar). "IC50MicroM" specifies activities as the 50 inhibitory concentration (micromolar).
onlyCellMinerExps

a logical value indicating whether to only return experimental data included in CellMiner (default=TRUE).

Value

a table of activity range statistics for a set of compounds.

Examples

nscSet <- c("609699", "740")
getActivityRangeStats(nscSet)
getActivityRangeStats(nscSet, concFormat="IC50MicroM")

Returns a list of feature data matrices.

Description

Returns a list of feature data matrices.

Usage

getAllFeatureData(object, ...)

Arguments

object

Object for which a list of feature data matrices is to be returned.
...

Other possible parameters.

Value

A list of feature data matrices.

Returns a list of feature data matrices.

Description

Returns a list of feature data matrices.

Usage

## S4 method for signature 'MolData'
getAllFeatureData(object)

Arguments

object

MolData object for which a list of feature data matrices is to be returned.

Value

A list of feature data matrices.

Compute a binary gene mutation data matrix from SNP and other mutation event-level data.

Description

Compute a binary gene mutation data matrix from SNP and other mutation event-level data.

Usage

getBinaryMutationData(
  mutInfo,
  mutData,
  maxVariantFreq = 0.2,
  maxNormalPopulationFreq = 0.005,
  maxSiftScore = 0.05,
  minPolyPhenScore = 0.85
)

Arguments

mutInfo

A data frame with the following named columns: Gene, the name of the gene associated with the mutation event; probe.ids, a unique identifier specifying the mutation event; SNP_1000_genome, the frequency of the mutation event in SNP 1000; ESP5400, the frequency of the mutation event in ESP5400; SNP_type, the type of mutation event, chosen from "MISSENSE", "FRAMESHIFT", "NONFRAMESHIFT", "NONSENSE", "SPLICING"; SIFT_score, the SIFT score; Polyphen_score, the POLYPHEN score. Rownames of mutInfo should be set to probe.ids, i.e., the unique mutation event specifier.
mutData

A matrix with event level mutation information, with SNPs, etc. along rows and samples along columns. Rownames of mutData should exactly match those of mutInfo. The i-th row of mutInfo should thus give detailed information for the mutation event with data specified in the i-th row of mutData.
maxVariantFreq

The maximum proportion of mutant samples (used to exclude frequently occuring events); default value = 0.2.
maxNormalPopulationFreq

The maximum freqency of a mutation in the normal population (used to exclude likely germline variants); default value = 0.005.
maxSiftScore

The maximum accepted SIFT score (used to exclude presumed non-deleterious mutations); default value = 0.05.
minPolyPhenScore

The minimum accepted POLYPHEN score (used to exclude presumed non-deleterious mutations); default value = 0.85.

Value

A binary gene mutation matrix, with genes along rows, samples along columns, and 1s indicating deleterious mutations.

Calculate quantile for the columns in a matrix

Description

Calculate quantile for the columns in a matrix

Usage

getColumnQuantiles(X, prob, naRm = FALSE, onlyNonzeroVals = FALSE)

Arguments

X

the matrix
prob

a numeric probablity
naRm

a boolean, whether to remove NAs
onlyNonzeroVals

a boolean, whether to only include non-zero values

Value

a vector of quantiles

Examples

getColumnQuantiles(matrix(1:25, nrow=5), prob = 0.5)

Returns a matrix containing activity (-logGI50) data for a set of compounds.

Description

Returns a matrix containing activity (-logGI50) data for a set of compounds.

Usage

getDrugActivityData(nscSet, onlyCellMinerExps = TRUE)

Arguments

nscSet

A string specifying the NSC identifiers for the compounds.
onlyCellMinerExps

A logical value indicating whether to compute results using only experimental data included in CellMiner (default=TRUE).

Value

a matrix with NCI-60 average (over experiments) -logGI50 activity data; compound activity profiles are along rows.

Examples

nscSet <- c("141540", "123127") # Etoposide, Doxorubicin.
actData <- getDrugActivityData(nscSet)

Returns a vector of log activity range values for set of compounds.

Description

Returns a vector of log activity range values for set of compounds.

Usage

getDrugActivityRange(nscSet, computeIQR = FALSE)

Arguments

nscSet

a character vector specifying NSC identifier(s) for compound(s) of interest.
computeIQR

logical value indicated whether inter-quartile range is to be computed; otherwise absolute range is computed (default=FALSE).

Value

a numeric vector of NCI-60 log activity (-logGI50) range values indexed by the identifiers in nscSet.

Examples

nscSet <- c("609699", "740")
getDrugActivityRange(nscSet)

Returns a matrix containing repeat activity experiment data for a compound.

Description

Returns a matrix containing repeat activity experiment data for a compound.

Usage

getDrugActivityRepeatData(
  nscStr,
  concFormat = "NegLogGI50M",
  onlyCellMinerExps = TRUE
)

Arguments

nscStr

a string specifying the NSC identifier for the compound.
concFormat

a string selected from "NegLogGI50M" or "IC50MicroM". "NegLogGI50M" specifies activities as the negative log of the 50 inhibitory concentration (molar). "IC50MicroM" specifies activities as the 50 growth inhibitory concentration (micromolar).
onlyCellMinerExps

a logical value indicating whether to only return experimental data included in CellMiner (default=TRUE).

Value

a matrix with activity data from each experiment associated with a compound organized along the rows.

Examples

nscStr <- "609699"
actData <- getDrugActivityRepeatData(nscStr, concFormat='NegLogGI50M')
actData <- getDrugActivityRepeatData(nscStr, concFormat='IC50MicroM')

Get a list of applicable MOA strings for a drug.

Description

Get a list of applicable MOA strings for a drug.

Usage

getDrugMoaList(nsc, moaToCompoundListMap = NULL)

Arguments

nsc

An NSC string.
moaToCompoundListMap

A named list of character vectors, with each name indicating an MOA class, and its corresponding character vector specifying MOA-associated drugs. If unspecified, this is constructed based on MOA information provided by CellMiner.

Details

LINK TO MOAs?

Value

A character vector giving all MOA classes for the drug.

Examples

getDrugMoaList("754365")

Get the drug names for a set of NSC identifiers.

Description

Get the drug names for a set of NSC identifiers.

Usage

getDrugName(nscSet)

Arguments

nscSet

A character vector of NSC strings

Value

A named character vector indicating the compound names for each NSC in nscSet (with an empty string returned if no such information is available, and an NA returned if the NSC is not included in the CellMiner database).

Examples

nscSet <- c("609699", "94600")
getDrugName(nscSet)

Returns a list of eSet objects.

Description

Returns a list of eSet objects.

Usage

getESetList(object, ...)

Arguments

object

Object for which a list of eSets is to be returned.
...

Other possible parameters.

Value

A list of eSet objects.

Returns a list of eSet objects.

Description

Returns a list of eSet objects.

Usage

## S4 method for signature 'MolData'
getESetList(object)

Arguments

object

MolData object for which a list of eSet objects is to be returned.

Value

A list of eSet objects.

Returns a list of data frames with feature information.

Description

Returns a list of data frames with feature information.

Usage

getFeatureAnnot(object, ...)

Arguments

object

Object for which feature data is to be returned.
...

Other possible parameters.

Value

A list of data frames with feature information.

Returns a list of data frames with feature information.

Description

Returns a list of data frames with feature information.

Usage

## S4 method for signature 'DrugData'
getFeatureAnnot(object)

Arguments

object

DrugData object for which feature data is to be returned.

Value

A named list of data frames with feature information for drugs and drug repeat experiments.

Returns a list of data frames with feature information.

Description

Returns a list of data frames with feature information.

Usage

## S4 method for signature 'MolData'
getFeatureAnnot(object)

Arguments

object

MolData object for which feature data is to be returned.

Value

A named list of data frames with feature information for available molecular data types.

Extract from a list of matrices the data associated with a set of features.

Description

Extract from a list of matrices the data associated with a set of features.

Usage

getFeatureDataFromMatList(
  featureSet,
  dataMatList,
  excludeMissingFeatures = TRUE
)

Arguments

featureSet

a character vector of feature names.
dataMatList

a list of matrices with feature data organized along the rows, and feature names accessible via rownames(dataMatList).
excludeMissingFeatures

a logical value indicating whether features whose data cannot be found in any matrices in dataMatList should be excluded in the output. (default=TRUE).

Value

a single matrix containing data for all features in featureSet.

Examples

featureSet <- c("expSLFN11", "mutSLX4")
molDataMats <- getMolDataMatrices()
featureData <- getFeatureDataFromMatList(featureSet, molDataMats)

Returns a vector of median sensitive cell line activity (-logGI50) values for a set of compounds.

Description

Returns a vector of median sensitive cell line activity (-logGI50) values for a set of compounds.

Usage

getMedSenLineActivity(
  idSet,
  senLineActZThreshold = 0.5,
  onlyCellMinerExps = TRUE,
  dataSource = "NCI60"
)

Arguments

idSet

a character vector specifying identifier(s) for compound(s) of interest.
senLineActZThreshold

the minimum activity z-score for a sensitive cell line (default=0.5).
onlyCellMinerExps

a logical value indicating whether to base results strictly on experimental data included in CellMiner (default=TRUE).
dataSource

character string indicating data source (default="NCI60"). Currently only "NCI60" is supported.

Value

a numeric vector of median sensitive cell line activity (-logGI50) values indexed by the identifiers in idSet.

Examples

idSet <- c("609699", "740")
getMedSenLineActivity(idSet)

Returns a table indicating, for each compound in a specified set, the least significant correlation and associated p-value between its replicate experiments.

Description

Returns a table indicating, for each compound in a specified set, the least significant correlation and associated p-value between its replicate experiments.

Usage

getMinDrugActivityRepeatCor(nscSet)

Arguments

nscSet

a character vector specifying NSC identifier(s) for compound(s) of interest.

Value

a dataframe containing the following columns: NSC, cor, pval

Examples

nscSet <- c("123528", "339316")
repExpCorTab <- getMinDrugActivityRepeatCor(nscSet)

Get MOA string

Description

Get MOA string

Usage

getMoaStr(nscStr)

Arguments

nscStr

an NSC string

Details

LINK TO MOAs?

Value

a comma-delimited string with MOA

Examples

getMoaStr("94600")
getMoaStr(c("94600", "609699"))

Get a named list mapping MOA classes to associated compound sets.

Description

Get a named list mapping MOA classes to associated compound sets.

Usage

getMoaToCompounds()

Value

a named list mapping MOA classes to associated compound sets (each represented as a character vector).

Examples

moaToCompounds <- getMoaToCompounds()

Returns a list of molecular data type matrices, with rownames in each matrix prefixed with a data type abbreviation.

Description

Returns a list of molecular data type matrices, with rownames in each matrix prefixed with a data type abbreviation.

Usage

getMolDataMatrices(molDataMats = NULL)

Arguments

molDataMats

A named list of molecular data type matrices with feature data specified along the rows, and feature names indicated in the row names.

Value

a list containing molecular data type matrices, with rownames in each matrix prefixed with a data type abbreviation, e.g., 'exp' for mRNA expression, etc. The matrix-specific data type abbreviations are derived from the names of molDataMats.

Examples

molDataMats <- getMolDataMatrices()

Get the molecular data type prefixes for a set of features.

Description

Get the molecular data type prefixes for a set of features.

Usage

getMolDataType(features, prefixLen = 3)

Arguments

features

A vector of features.
prefixLen

The length of the molecular data type prefix.

Value

A character vector of molecular data type prefixes.

#' @examples getMolDataType(c("expTP53", "copMDM2", "mutCHEK2", "mutBRAF"))

Returns a vector indicating the number of drug activity repeat experiments with available data for each member of a set of compounds.

Description

Returns a vector indicating the number of drug activity repeat experiments with available data for each member of a set of compounds.

Usage

getNumDrugActivityRepeats(nscSet, onlyCellMinerExps = TRUE)

Arguments

nscSet

a character vector specifying NSC identifier(s) for compound(s) of interest.
onlyCellMinerExps

a logical value indicating whether to return only the number of experiments with data included in CellMiner (default=TRUE).

Value

a numeric vector, indexed by nscSet, indicating the number of drug activity repeat experiments for each one of its compounds.

Examples

nscSet <- c("1", "17", "89", "609699")
getNumDrugActivityRepeats(nscSet)

Returns a vector indicating the number of NCI-60 cell lines with missing activity data for set of compounds.

Description

Returns a vector indicating the number of NCI-60 cell lines with missing activity data for set of compounds.

Usage

getNumMissingLines(nscSet)

Arguments

nscSet

a character vector specifying NSC identifier(s) for compound(s) of interest.

Value

a numeric vector indicating the number of NCI-60 cell lines with missing activity data, indexed by the identifiers in nscSet.

Examples

nscSet <- c("1", "17", "89", "609699")
getNumMissingLines(nscSet)

Returns an eSet object with drug repeat activity experiment data.

Description

Returns an eSet object with drug repeat activity experiment data.

Usage

getRepeatAct(object, ...)

Arguments

object

Object for which drug repeat activity experiment data is to be returned.
...

Other possible parameters.

Value

An eSet object with drug repeat activity experiment data.

Returns an eSet object with drug repeat activity experiment data.

Description

Returns an eSet object with drug repeat activity experiment data.

Usage

## S4 method for signature 'DrugData'
getRepeatAct(object)

Arguments

object

DrugData object for which drug repeat activity experiment data is to be returned.

Value

An eSet object with drug repeat activity experiment data.

Computes the relative standard deviation values with respect to the columns of a matrix or data.frame.

Description

Computes the relative standard deviation values with respect to the columns of a matrix or data.frame.

Usage

getRsd(dat, onlyReturnMedian = TRUE)

Arguments

dat

a matrix or data.frame with numeric values.
onlyReturnMedian

a logical value indicating whether only the median column RSD value should be returned (vs. all RSD values).

Value

median RSD value over the data set columns or all RSD values, depending on value of onlyReturnMedian (default=TRUE).

Examples

A <- matrix(rnorm(10*60), nrow=10)
getRsd(A)
getRsd(A, onlyReturnMedian=FALSE)

Returns a data frame with sample information.

Description

Returns a data frame with sample information.

Usage

getSampleData(object, ...)

Arguments

object

Object for which sample data is to be returned.
...

Other possible parameters.

Value

A data frame with sample information.

Returns a data frame with sample information.

Description

Returns a data frame with sample information.

Usage

## S4 method for signature 'DrugData'
getSampleData(object)

Arguments

object

DrugData object for which sample data is to be returned.

Value

A data frame with sample information.

Returns a data frame with sample information.

Description

Returns a data frame with sample information.

Usage

## S4 method for signature 'MolData'
getSampleData(object)

Arguments

object

MolData object for which sample data is to be returned.

Value

A data frame with sample information.

Get the SMILES strings for a set of NSC identifiers.

Description

Get the SMILES strings for a set of NSC identifiers.

Usage

getSmiles(nscSet)

Arguments

nscSet

A character vector of NSC strings

Value

A named character vector indicating the SMILES string for each NSC in nscSet (or NA if no structural information is available).

Examples

nscSet <- c("609699", "94600")
getSmiles(nscSet)

Check if NSC has Mechanism of Action (MOA) Annotation

Description

Check if NSC has Mechanism of Action (MOA) Annotation

Usage

hasMoa(nsc)

Arguments

nsc

a string, an NSC identifier

Value

a boolean whether the NSC has an MOA

Examples

hasMoa("754365")

Returns a DrugData object.

Description

Returns a DrugData object.

Usage

## S4 method for signature 'DrugData'
initialize(.Object, act, repeatAct, sampleData)

Arguments

.Object

An object: see "new()" documentation in "methods" package.
act

An eSet object containing drug activity data across a set of biological samples.
repeatAct

An eSet object containing repeat drug activity experiment data with respect to the same samples associated with act.
sampleData

A MIAxE object capturing sample and other data set information.

Value

A DrugData object.

Note

Seems to be required for definition of a constructor.

Returns a MolData object.

Description

Returns a MolData object.

Usage

## S4 method for signature 'MolData'
initialize(.Object, eSetList, sampleData)

Arguments

.Object

An object: see "new()" documentation in "methods" package.
eSetList

A list of eSet objects for a common set of samples.
sampleData

A MIAxE object capturing sample and other data set information.

Value

A MolData object.

Check if an NSC ID is public

Description

Check if an NSC ID is public

Usage

isPublic(nscs)

Arguments

nscs

a vector of NSC string IDs

Value

a vector of boolean values of whether each NSC is public

Examples

isPublic("-1")
isPublic(c("-1", "609699"))

Returns data to plot CellMiner plots

Description

Returns data to plot CellMiner plots

Usage

loadCellminerPlotInfo(returnDf = FALSE)

Arguments

returnDf

a boolean if a data.frame with all information (default: FALSE)

Value

a vector of colors as strings or a data.frame with dataType, label, xMin, xMax

Examples

loadCellminerPlotInfo()

Returns a 60-element color set that matches the color set used on http://discover.nci.nih.gov/

Description

Returns a 60-element color set that matches the color set used on http://discover.nci.nih.gov/

Usage

loadNciColorSet(returnDf = FALSE)

Arguments

returnDf

a boolean if a data.frame with tissue names and abbreviations should be returned (default: FALSE)

Value

a vector of colors as strings or a data.frame with tissues, tissue abbreviations, cell line abbreviations and colors

Examples

loadNciColorSet()

Returns a MolData object.

Description

Returns a MolData object.

Usage

MolData(eSetList, sampleData, ...)

Arguments

eSetList

A list of eSet objects for a common set of samples.
sampleData

A MIAxE object capturing sample and other data set information.
...

Other possible parameters.

Value

A MolData object.

An S4 class to represent molecular data recorded for a set of biological samples.

Description

An S4 class to represent molecular data recorded for a set of biological samples.

Arguments

...

Other possible parameters.

Slots

eSetList

A list of eSet objects for a common set of samples.

sampleData

A MIAxE object capturing sample and other data set information.

Returns a MolData object.

Description

Returns a MolData object.

Usage

## S4 method for signature 'list,MIAxE'
MolData(eSetList, sampleData, ...)

Arguments

eSetList

A list of eSet objects for a common set of samples.
sampleData

A MIAxE object capturing sample and other data set information.
...

Other possible parameters.

Value

A MolData object.

Compare an input pattern against a set of patterns, excluding the predictive effect of a fixed pattern or set of patterns.

Description

Compare an input pattern against a set of patterns, excluding the predictive effect of a fixed pattern or set of patterns.

Usage

parCorPatternComparison(x, Y, Z, updateProgress = NULL)

Arguments

x

An N element input pattern specified as either a vector or a 1 x N matrix or data frame.
Y

An N element pattern specified as a vector for comparison with the input pattern x or a k x N matrix with k patterns for comparison with the input pattern x specified along the rows, with rownames set appropriately.
Z

An N element pattern specified as a vector or a k x N matrix of patterns specified along the rows. These are the patterns whose effect (with respect to a linear model) is to be excluded when comparing x with Y or each row entry of Y. Note that for the partial correlation to be value, the pattern(s) in Z should not overlap with those in x or Y.
updateProgress

A optional function to be invoked with each computed partial correlation to indicate progress.

Value

A data frame with pattern comparison results (ordered by PARCOR): NAME: Name of entry in Y being compared. PARCOR: Partial correlation between x and the entry in Y with respect to Z. PVAL: p-value.

Examples

x <- exprs(getAct(rcellminerData::drugData))["609699", ]
Y <- rcellminer::getAllFeatureData(rcellminerData::molData)[["exp"]][1:100, ]
Z <- rcellminer::getAllFeatureData(rcellminerData::molData)[["exp"]][c("SLFN11", "JAG1"), ]
results <- parCorPatternComparison(x, Y, Z)
Y <- rcellminer::getAllFeatureData(rcellminerData::molData)[["exp"]][1, , drop=TRUE]
Z <- rcellminer::getAllFeatureData(rcellminerData::molData)[["exp"]]["SLFN11", , drop=TRUE]
results <- parCorPatternComparison(x, Y, Z)

Compare an input pattern against a set of patterns.

Description

Compare an input pattern against a set of patterns.

Usage

patternComparison(pattern, profileMatrixList, method = "pearson")

Arguments

pattern

An N element input pattern specified as either a named vector or an 1 x N matrix or data frame. Names (or column names) must match the column names of each element of profileMatrixList.
profileMatrixList

A single matrix (or data frame) or a list of matrices (or data frames). Each matrix (data frame) must be k x N - that is the k patterns for comparison with the input pattern must be specified along the rows, with rownames set appropriately.
method

a string specifying the type of correlation, chosen from pearson (default) or spearman.

Value

A data frame with pattern comparison results. Specifically, if M is the total number patterns in profileMatrixList elements, an M x 2 matrix is returned with sorted Pearson's correlations in the first column and corresponding p-values in the second column. Comparison pattern names are indicated in the row names.

Examples

drugAct <- exprs(getAct(rcellminerData::drugData))
molDataMats <- getMolDataMatrices()[c("exp", "mut")]
molDataMats <- lapply(molDataMats, function(X) X[1:10, ])
pcResults <- patternComparison(drugAct["609699", ], molDataMats)
pcResults <- patternComparison(drugAct["609699", ], molDataMats, method="spearman")
pcResults <- patternComparison(drugAct["609699", ], molDataMats$exp, method="spearman")

Description: Produces CellMiner-like plots in R

Description

Description: Produces CellMiner-like plots in R

Usage

plotCellMiner(
  drugAct,
  molData,
  plots,
  nsc = NULL,
  gene = NULL,
  features = NULL,
  sub = NULL,
  xLimits = NULL,
  xLabel = NULL,
  extraPlot = NULL,
  verbose = FALSE
)

Arguments

drugAct

a matrix of drug activity values (cell lines as columns, drug entries as rows)
molData

a list of matricies a molecular
plots

a vector of characters denoting the plots to include and the order (e.g. c("mut", "drug", "cop"). Currently, supported entries mutations (mut), drug activities (drug), copy number variations (cop)
nsc

a string NSC ID that will be plotted when a "drug" entry appears in the plots vector
gene

a string HUGO gene symbol for which the "mut", "cop", or "exp" plots will be produced if in plots vector
features

a vector of strings that provide the full IDs for elements to be plotted (e.g. mutCDK4 for CDK4 mutations). This overwrites the nsc and gene parameters, but is needed in advanced plots that involve data that involves one-to-many relationships (e.g. many entries for a given gene in the exome data) and a gene symbol is ambiguous.
sub

a vector of strings with sub-titles for each plot
xLimits

a 2 number vector with the the minimum and maximum X-axis values (default: -3,3 for Z-scores, 0,1 for binary entries)
xLabel

a string for the default X-axis label
extraPlot

a list containing title, label, and values (numeric vector of length 60); only one extra plot can be included
verbose

a boolean to show debugging information

Value

None

Author(s)

Augustin Luna <augustin AT mail.nih.gov>

Examples

drugAct <- exprs(getAct(rcellminerData::drugData))
molData <- getMolDataMatrices()
plots <- c("mut", "drug", "cop", "xai", "pro")
plotCellMiner(drugAct, molData, plots=plots, nsc="94600", gene="CDK4", verbose=FALSE)

plots <- c("mut", "xai", "cop", "cop", "cop", "cop")
plotCellMiner(drugAct, molData, plots=plots, nsc="94600", gene=c("CDK4", "TP53", 
  "BRAF", "GAPDH"), verbose=FALSE)

plotCellMiner(drugAct, molData, plots=NULL, nsc=NULL, features=c("mutCDK4", 
  "xaiCDK4", "exochr1:101704532_G_T", "mdaIS_P53_MUT", "mirhsa-miR-22", "proTP53_26_GBL00064"), 
  verbose=FALSE)

Make a simple 2d plot using two variables with ggplot2

Description

Make a simple 2d plot using two variables with ggplot2

Usage

plotCellMiner2D(
  df,
  xCol = "x",
  yCol = "y",
  xLabel = xCol,
  yLabel = yCol,
  title = NULL,
  colorPalette = NULL,
  classCol = NULL,
  tooltipCol = NULL,
  showLegend = FALSE,
  showTrendLine = TRUE,
  showTitle = TRUE,
  singleColor = "#0000FF",
  alpha = 1,
  numberColPrefix = "X",
  xLimVal = NULL,
  yLimVal = NULL,
  pointSize = 3
)

Arguments

df

a data.frame with at least two columns
xCol

the name of the column in df with the "x" data. See Note
yCol

the name of the column in df with the "y" data. See Note
xLabel

the x plot label
yLabel

the y plot label
title

the plot title, if null the correlation will appear (DEFAULT: NULL)
colorPalette

a named vector with the names classes and value colors (DEFAULT: NULL)
classCol

the name of the column with the classes. Values in column of df must be a factor (DEFAULT: NULL)
tooltipCol

the name of the column used for tooltips when plotted with plotly
showLegend

boolean, whether to show the legend (DEFAULT: FALSE)
showTrendLine

boolean, whether to show the trendline
showTitle

boolean, whether to show the title
singleColor

a color to be used for all points when a color palette is not provided (DEFAULT: blue)
alpha

value from 0-1, where 0 indicates transparent points (DEFAULT: 1, not transparent)
numberColPrefix

a prefix to add to column names that start with a number that causes issues with ggplot (DEFAULT: X)
xLimVal

a two entry vector (min, max) to set the x-axis
yLimVal

a two entry vector (min, max) to set the y-axis
pointSize

size of points on plot (DEFAULT: 3)

Value

a ggplot object

Note

TROUBLESHOOTING NOTES: 1) Avoid ":" in colnames

Uses ggplot aes_string() which uses parse() to turn your text expression into a proper R symbol that can be resolved within the data.frame. Avoid numbers and spaces in

Author(s)

Augustin Luna <augustin AT mail.nih.gov>

Examples

## Not run: 
# Load data
nci60DrugActZ <- exprs(getAct(rcellminerData::drugData))
nci60GeneExpZ <- getAllFeatureData(rcellminerData::molData)[["exp"]]
# Load colors
colorTab <- loadNciColorSet(returnDf=TRUE)
tissueColorTab <- unique(colorTab[, c("tissues", "colors")])
# Merge data
df <- as.data.frame(t(rbind(nci60DrugActZ["94600",], nci60GeneExpZ["SLFN11",])))
colnames(df) <- c("y", "x")
df <- cbind(df, colorTab)
# Plot data
plotCellMiner2D(df, xCol="x", yCol="y", xLabel="SLFN11", yLabel="94600")
plotCellMiner2D(df, xCol="x", yCol="y", showTrendLine = FALSE, showTitle = FALSE)
plotCellMiner2D(df, xCol="x", yCol="y", showTrendLine = FALSE, showLegend = FALSE)

## End(Not run)

Plot NCI-60 drug activity profiles for repeat experiments.

Description

Plot NCI-60 drug activity profiles for repeat experiments.

Usage

plotDrugActivityRepeats(
  nscStr,
  useZScore = FALSE,
  maxRepNum = 5,
  pdfFilename = NULL,
  pdfWidth = 12,
  pdfHeight = 6
)

Arguments

nscStr

a string specifying the NSC identifier for a compound.
useZScore

a boolean specifying whether to plot z-transformed data (as opposed to -logGI50 values).
maxRepNum

an integer specifying the maximum number of repeat experiments to plot.
pdfFilename

name of a PDF output
pdfWidth

with of the PDF (default: 12)
pdfHeight

with of the PDF (default: 6)

Value

NONE

Examples

plotDrugActivityRepeats("609699")
plotDrugActivityRepeats("609699", useZScore=TRUE, maxRepNum=3)

Produces a barplot of the average values for a set of NSCs with a error bar (one standard deviation)

Description

Produces a barplot of the average values for a set of NSCs with a error bar (one standard deviation)

Usage

plotDrugSets(
  drugAct,
  drugs,
  mainLabel = "",
  pdfFilename = NULL,
  statistic = "mean"
)

Arguments

drugAct

a matrix of drug activity values (cell lines as columns, drug entries as rows)
drugs

a vector of NSC IDs whose values will be averaged by cell line
mainLabel

a main label for the plot
pdfFilename

a string file name for a PDF plot, no file output will be produced if this is not provided
statistic

a string, either 'mean' or 'median' (Default: mean)

Value

no values are returned

Examples

drugAct <- exprs(getAct(rcellminerData::drugData))
drugs <- rownames(drugAct)[1:8]
plotDrugSets(drugAct, drugs, "Test")

Remove molecular data type prefixes from features.

Description

Remove molecular data type prefixes from features.

Usage

removeMolDataType(features, prefixLen = 3)

Arguments

features

A vector of features.
prefixLen

The length of the molecular data type prefix.

Details

This function is primarily used to remove prefixes from elastic net features.

Value

A named vector of features without molecular data type prefixes.

Examples

removeMolDataType(c("expTP53", "copMDM2", "mutCHEK2", "mutBRAF"))

Restricts a feature matrix to only include features associated with a specified gene set.

Description

Restricts a feature matrix to only include features associated with a specified gene set.

Usage

restrictFeatureMat(geneSet, featureMat, prefixSet = c("cop", "exp", "mut"))

Arguments

geneSet

a character vector of gene names.
featureMat

a matrix or data frame with feature vectors along rows and feature names specified in rownames(featureMat).
prefixSet

a set of feature name prefixes to be prepended to each element of geneSet to obtain a collection of geneSet-associated features.

Value

a matrix containing the features in the intersection of rownames(featureMat) and the set of geneSet-derived features (obtained by prepending each element of prefixSet to each gene in geneSet).

#' @examples X <- matrix(1:25, nrow=5) rownames(X) <- c("expA", "expB", "copC", "mutC", "expD") restrictFeatureMat(geneSet = c("B", "C"), X)

Row-wise correlations

Description

Correlation between ith row of x and ith row of y for all i

Usage

rowCors(X, Y)

Arguments

X

a matrix
Y

a matrix

Value

a list of two vectors: cor (correlation values) and pval (correlation p-values)

Author(s)

Sudhir Varma, NCI-LMP

Examples

a <- matrix(runif(100), nrow=10, ncol=10)
b <- matrix(runif(100), nrow=10, ncol=10)
c <- rowCors(a, b)

Search for NSCs

Description

Search for NSCs

Usage

searchForNscs(pattern)

Arguments

pattern

a search pattern. This string will be treated as a regular expression with the case ignored.

Details

Use this function with caution. Not all compounds have names and compounds can have many synonyms not included in CellMiner.

Value

A vector of matching NSCs

Examples

searchForNscs("nib$")

Select features that are correlated with a given feature (or one or more features from a set of features).

Description

Select features that are correlated with a given feature (or one or more features from a set of features).

Usage

selectCorrelatedRows(Y, X, corThreshold = 0.1, useAbsCor = TRUE)

Arguments

Y

a vector or matrix; rows from X will be correlated with Y if Y is a vector or with rows of Y, if Y is a matrix.
X

a matrix of values that will be compared with Y (vector) or rows of Y (matrix)
corThreshold

the minimum correlation threshold for the row to be returned
useAbsCor

a logical value indicating whether absolute correlations should be used (default=TRUE).

Value

a matrix of rows of X correlated with Y (if Y is a vector) or correlated with at least one row of Y if Y is a matrix or data frame.

Examples

vec <- runif(10)
mat <- matrix(runif(100), 10, 10)
selectCorrelatedRows(vec, mat)

Select features that are correlated with a given feature (or one or more features from a set of features), merging results from multiple candidate feature matrices.

Description

Select features that are correlated with a given feature (or one or more features from a set of features), merging results from multiple candidate feature matrices.

Usage

selectCorrelatedRowsFromMatrices(
  Y,
  XList,
  corThreshold = 0.1,
  useAbsCor = TRUE
)

Arguments

Y

a vector or matrix; rows from each matrix element of X will be correlated with Y if Y is a vector or with rows of Y, if Y is a matrix.
XList

a list of matrices whose rows will be correlated with Y (vector) or rows of Y (matrix). The rownames in each matrix element of XList must be specified to values that are unique with respect to the total set of rownames (as derived from all matrices in XList).
corThreshold

the minimum correlation threshold for the row to be returned
useAbsCor

a logical value indicating whether absolute correlations should be used (default=TRUE).

Value

a matrix formed from rows of matrices in XList that are correlated with Y (if Y is a vector) or correlated with at least one row of Y if Y is a matrix or data frame.

Examples

vec <- runif(10)
names(vec) <- 1:10
matList <- list(X1 = matrix(runif(100), 10, 10), X2 = matrix(runif(100), 10, 10))
rownames(matList$X1) <- paste0("X1_row_", 1:10)
colnames(matList$X1) <- paste0("X1_col_", 1:10)
rownames(matList$X2) <- paste0("X2_row_", 1:10)
colnames(matList$X2) <- paste0("X2_col_", 1:10)
selectCorrelatedRowsFromMatrices(vec, matList)