Decipher Mutational Signatures from Somatic Mutational Catalogs.

Description

Cancer cells accumulate DNA mutations as result of DNA damage and DNA repair pro-cesses. mutSignatures is a computational framework that is aimed at deciphering DNA mutational signatures oper-ating in cancer. The input is a numeric matrix of DNA mutation counts de-tected in a panel of cancer samples. The framework performs Non-negative Matrix Factorization to extract mutational signatures explaining the observed set of DNA mutations. The framework relies on parallelization and is optimized for use on multi-core systems. This framework was described by Fantini D et al (2020) https://www.nature.com/articles/s41598-020-75062-0/ and is built upon a custom R-based implementation of the original MATLAB WTSI frame-work by Alexandrov LB et al (2013) https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3588146/. The mutSignatures framework has been described in peer-reviewed publications, including Fantini D et al (2018) https://www.nature.com/articles/s41388-017-0099-6/ and Fantini D et al (2019) https://www.sciencedirect.com/science/article/abs/pii/S1078143918303818/. The framework includes three modules that support raw data import and pre-processing, mutation counts deconvolution, and data visualization.

References

More info, examples and vignettes:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. 2020 Sci Rep paper describing the latest version of mutSignatures: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper: Mutational Signatures operative in bladder cancer: https://www.nature.com/articles/s41388-017-0099-6/

Subset a mutSignExposures-class object.

Description

Subset a mutSignExposures-class object.

Usage

## S4 method for signature 'mutSignExposures,numeric,ANY,ANY'
x[i]

Arguments

Subset a mutationCounts-class object.

Description

Subset a mutationCounts-class object.

Usage

## S4 method for signature 'mutationCounts,numeric,ANY,ANY'
x[i]

Arguments

Subset a mutationSignatures-class object.

Description

Subset a mutationSignatures-class object.

Usage

## S4 method for signature 'mutationSignatures,numeric,ANY,ANY'
x[i]

Arguments

Add Weak Mutation TYpes

Description

Restore Mutation Types that were initially excluded because a low number of total counts.

Usage

addWeak(
  mutationTypesToAddSet,
  processes_I,
  processesStd_I,
  Wall_I,
  genomeErrors_I,
  genomesReconstructed_I
)

Arguments

Details

This is one of the core functions included in the original mutSignatures R library, and in the WTSI MATLAB framework. This is an internal function.

Value

Output is the final result of the deconvolution process

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. WTSI framework: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3588146/

Perform Non-negative Matrix Factorization using Brunet's Algotithm.

Description

Perform Non-negative Matrix Factorization.

Usage

alexaNMF(v, r, params)

Arguments

Details

This is one of the core functions included in the original mutSignatures R library, and in the WTSI MATLAB framework. This is an internal function.

Value

list including all paramaters for running the analysis:

1. W extracted signatures

2. H contribution of each signature in all the samples of the input mut count matrix

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. WTSI framework: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3588146/

Examples

x <- mutSignatures:::getTestRunArgs("alexaNMF")
y <- mutSignatures:::alexaNMF(v = x$v, r = x$r, params = x$params)
y$w[1:5, ]

Convert and/or transpose a mutSignExposures object to data.frame.

Description

Coerce a mutSignExposures-class object to data.frame by applying the coerceObj method. The data.frame can be returned in a transposed or non-transposed format.

Usage

## S4 method for signature 'mutSignExposures'
as.data.frame(x, row.names = NULL, optional = NULL, ...)

Arguments

Convert a mutationCounts object to data.frame.

Description

Coerce a mutationCounts-class object to data.frame by applying the coerceObj method.

Usage

## S4 method for signature 'mutationCounts'
as.data.frame(x)

Arguments

Convert a mutationSignatures object to data.frame.

Description

Coerce a mutationSignatures-class object to data.frame by applying the coerceObj method.

Usage

## S4 method for signature 'mutationSignatures'
as.data.frame(x)

Arguments

Convert a mutFrameworkParams object to list.

Description

Coerce a mutFrameworkParams-class object to list by applying the coerceObj method.

Usage

## S4 method for signature 'mutFrameworkParams'
as.list(x)

Arguments

Convert a mutationSignatures object to list.

Description

Coerce a mutationSignatures-class object to list by applying the coerceObj method.

Usage

## S4 method for signature 'mutationSignatures'
as.list(x)

Arguments

Convert a mutationCounts object to matrix.

Description

Coerce a mutationCounts-class object to matrix by applying the coerceObj method.

Usage

## S4 method for signature 'mutationCounts'
as.matrix(x)

Arguments

Method as.mutation.counts.

Description

Cast a data.frame into a mutationCounts-class object.

Usage

as.mutation.counts(x, rownames = NULL, colnames = NULL)

## S4 method for signature 'data.frame'
as.mutation.counts(x, rownames = NULL, colnames = NULL)

Arguments

Method as.mutation.signatures.

Description

Cast a data.frame into a mutationCounts-class object.

Usage

as.mutation.signatures(x)

## S4 method for signature 'data.frame'
as.mutation.signatures(x)

Arguments

Method as.mutsign.exposures.

Description

Cast a data.frame into a mutSignExposures-class object.

Usage

as.mutsign.exposures(x, samplesAsCols = TRUE)

## S4 method for signature 'data.frame,logical'
as.mutsign.exposures(x, samplesAsCols = TRUE)

Arguments

Attach Nucleotide Context.

Description

Retrieve the nucleotide context around each DNA variant based on the genomic coordinates of the variant and a reference BSGenome database.

Usage

attachContext(
  mutData,
  BSGenomeDb,
  chr_colName = "chr",
  start_colName = "start_position",
  end_colName = "end_position",
  nucl_contextN = 3,
  context_colName = "context"
)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

a modified data.frame including the nucleotide context in a new column

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Attach Mutation Types.

Description

Modify a data.frame carrying information about DNA mutation, and add a new column that stores formatted multi-nucleotide types.

Usage

attachMutType(
  mutData,
  ref_colName = "reference_allele",
  var_colName = "variant_allele",
  var2_colName = NULL,
  context_colName = "context",
  format = 1,
  mutType_dict = "alexa",
  mutType_colName = "mutType"
)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

a data.frame including a new column with mutation Types.

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Examples

 
A <- data.frame(REF = c("A", "T", "G"), 
                VAR = c("G", "C", "C"), 
                CTX = c("TAG", "GTG", "CGA"), 
                stringsAsFactors = FALSE)
mutSignatures::attachMutType(mutData = A, ref_colName = "REF", 
                             var_colName = "VAR", context_colName = "CTX")
      

Bootstrap a Mutation Count Matrix.

Description

Rearrange a Mutation count Matrix using the multivariate normal distribution. The function returns a bootstrapped Mutation Count matrix whose dimensions are identical to the input matrix.

Usage

bootstrapCancerGenomes(genomes, seed = NULL)

Arguments

Details

This is one of the core functions included in the original mutSignatures R library, and in the WTSI MATLAB framework. This is an internal function.

Value

a numeric matrix of bootstrapped Mutation Counts. Rows correspond to Mutation Types, columns to different samples.

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. WTSI framework: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3588146/

Examples

x <- cbind(c(10, 100, 20, 200, 30, 5), 
           c(100, 90, 80, 100, 11, 9))
mutSignatures:::bootstrapCancerGenomes(x)                

Combine two mutationSignatures-class objects.

Description

Combine two mutationSignatures-class objects.

Usage

## S4 method for signature 'mutationSignatures,mutationSignatures'
cbind2(x, y)

Arguments

Details

a variant of this method accepting more than 2 object to combine together is under preparation and be available soon...

Perform Non-negative Matrix Factorization using Chih-Jen Lin's Algotithm.

Description

Perform Non-negative Matrix Factorization (alternative approach).

Usage

chihJenNMF(v, r, params)

Arguments

Details

This is a core internal function.

Value

list including all paramaters for running the analysis:

1. W extracted signatures

2. H contribution of each signature in all the samples of the input mut count matrix

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. Chih-Jen Lin original paper: https://ieeexplore.ieee.org/document/4359171/

Examples

x <- mutSignatures:::getTestRunArgs("chihJenNMF")
y <- mutSignatures:::chihJenNMF(v = x$v, r = x$r, params = x$params)
y$w[1:10, ]

Method coerceObj.

Description

Cast an object to a different format, by extracting and returning the most appropriate information. Note that data.frames can be coerced to one of the classes defined in the mutSignatures package using coerceObj.

Usage

coerceObj(x, to, ...)

## S4 method for signature 'mutFrameworkParams,character'
coerceObj(x, to)

## S4 method for signature 'mutationSignatures,character'
coerceObj(x, to)

## S4 method for signature 'mutationCounts,character'
coerceObj(x, to, ...)

## S4 method for signature 'mutSignExposures,character'
coerceObj(x, to, ...)

## S4 method for signature 'data.frame,character'
coerceObj(x, to, ...)

Arguments

Count Mutation Types.

Description

Analyze a table (data.frame) including mutation counts. Count and aggregate Count Mutation Types. If multiple samples are included in the same table, results are aggregated by samples.

Usage

countMutTypes(mutTable, mutType_colName = "mutType", sample_colName = NULL)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

a mutationCounts-class object

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Examples

x <- mutSignatures:::getTestRunArgs("countMutTypes")
x
y <- mutSignatures::countMutTypes(mutTable = x, 
                                  mutType_colName = "mutation", 
                                  sample_colName = "sample")
y

Custom CSSLS.

Description

This function contributes to solving a nonnegative least square linear problem using normal equations and the fast combinatorial strategy from Van Benthem et al. (2004). This implementation is similar to that included in the NMF R package by Renaud Gaujoux and Cathal Seoighe, and it is tailored to the data used in the mutational signature analysis. For more info, see: https://CRAN.R-project.org/package=NMF

Usage

custom_cssls(CtC, CtA, Pset)

Arguments

Value

a numeric matrix

Examples

x <- mutSignatures:::getTestRunArgs(testN = "custom_cssls")
y <- mutSignatures:::custom_cssls(CtC = x$CtC, CtA = x$CtA, Pset = x$Pset)
y
 

Custom Fast Combinatorial Nonnegative Least-Square.

Description

This function contributes to solve a least square linear problem using the fast combinatorial strategy from Van Benthem et al. (2004). This implementation is similar to that included in the NMF R package by Renaud Gaujoux and Cathal Seoighe, and it is tailored to the data used in the mutational signature analysis. For more info, see: https://CRAN.R-project.org/package=NMF

Usage

custom_fcnnls(mutCounts, signatures)

Arguments

Value

list, including: (K) a numeric matrix of estimated exposures; and (Pset) a Pset numeric matrix

Examples

x <- mutSignatures:::getTestRunArgs(testN = "custom_fcnnls")
y <- mutSignatures:::custom_fcnnls(mutCounts = x$muts, signatures = x$signs)
y$coef
 

Decipher Mutational Processes Contributing to a Collection of Genomic Mutations.

Description

Decipher Mutational ProCancer cells accumulate DNA mutations as result of DNA damage and DNA repair processes. Thiscomputational framework allows to decipher mutational processes from cancer-derived somatic mutational catalogs.

Usage

decipherMutationalProcesses(input, params)

Arguments

Details

This is one of the core functions included in the original mutSignatures R library, and in the WTSI MATLAB framework. This is the main user interface for the mutSignatures analysis.

Value

list including all results of the analysis. The extracted signatures (processes) are included in the "processes" element of the list. The relative contribution of each signature in each sample is summarized in the "exposures" element.

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. WTSI framework: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3588146/

Examples

library(mutSignatures)
x <- mutSignatures:::getTestRunArgs("decipherMutationalProcesses")
x$muts
y <- mutSignatures::decipherMutationalProcesses(input = x$muts, 
                                                params = x$params)
y$Results$signatures

Deconvolute Mutation Counts.

Description

Characterize mutational signatures from cancer-derived somatic mutational catalogs.

Usage

deconvoluteMutCounts(input_mutCounts, params)

Arguments

Details

This is one of the core functions included in the original mutSignatures R library, and in the WTSI MATLAB framework. This is an internal function.

Value

list including all the results from the deconvolution analysis. This function is called within thedecipherMutationalProcesses() function after parameters and input data have been validated

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. WTSI framework: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3588146/

Examples

 
x <- mutSignatures:::getTestRunArgs("deconvoluteMutCounts")
y <- mutSignatures:::deconvoluteMutCounts(input_mutCounts = as.matrix(x$muts),
                                          params = as.list(x$params))
y$processes[1:10,]

Evaluate Results Stability.

Description

Perform a final Stability check comparing the results from all iterations of the analysis.

Usage

evaluateStability(wall, hall, params)

Arguments

Details

The function evaluates the results from all iterations by performing a silhouette check. A silhouette plot will also be plotted. This is one of the core functions included in the original mutSignatures R library, and in the WTSI MATLAB framework. This is an internal function.

Value

list including all results from the stability checks. This includes the most likely signatures (cen-troids) and exposures. All information for plotting the silhoueette plot will also be returned.

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. WTSI framework: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3588146/

Examples

# Obtain sample data
TMP <- mutSignatures:::getTestRunArgs("evaluateStability")
Y <- mutSignatures:::evaluateStability(wall = TMP$W, 
                                       hall = TMP$H, 
                                       params = TMP$params)

Extract Signatures from Genomic Mutational Catalogs.

Description

Extract mutational signatures after the input Data and the input parameters have been checked andvalidated.

Usage

extractSignatures(mutCountMatrix, params, bootStrap = TRUE)

Arguments

Details

This is one of the core functions included in the original mutSignatures R library, and in the WTSI MATLAB framework. This is an internal function.

Value

list including the following elements

1. Wall: all extracted signatures

2. Hall: all extracted exposures

3. mutCounts.reconstructed: fitted values

4. mutCounts.errors: residuals

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. WTSI framework: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3588146/

Examples

x <- mutSignatures:::getTestRunArgs("extractSignatures")
y <- mutSignatures:::extractSignatures(mutCountMatrix = as.matrix(x$muts), 
                                       params = as.list(x$params), bootStrap = TRUE)
y$Wk[1:10,]

Extract Variants from XvarlinkData.

Description

Extract Variants from data stored as XvarlinkData.

Usage

extractXvarlinkData(xvarLink_data)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

a data.frame including mutations as well as corresponding reference nucleotides.

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Examples

x <- mutSignatures:::getTestRunArgs("extractXvarlinkData")
y <- mutSignatures:::extractXvarlinkData(xvarLink_data = x)
y

            

Remove Iterations that Generated Outlier Results.

Description

Internal function from the WTSI framework, ported to R. This is a core function called from within a deconvoluteMutCounts() call. This function removes iterations that generated outlier results.

Usage

filterOutIterations(wall, hall, cnt_errors, cnt_reconstructed, params)

Arguments

Details

This is one of the core functions included in the original mutSignatures R library, and in the WTSI MATLAB framework. This is an internal function.

Value

list including all data required for running the subsequent stability check

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. WTSI framework: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3588146/

Filter Single Nucleotide Variants.

Description

Remove entries corresponding to non-SNV, such as insertions and deletions.

Usage

filterSNV(dataSet, seq_colNames)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

a filtered data.frame only including SNVs

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Examples

x <- mutSignatures:::getTestRunArgs("filterSNV")
nrow(x)
y <- mutSignatures::filterSNV(dataSet = x, 
                              seq_colNames = c("REF", "ALT"))
nrow(y)

                    

Convert Mutation COunts to PerMille Frequencies.

Description

Convert Mutation COunts to frequencies. Typically, a permille frequence is returned. In other words, the resulting number indicates the expected mutation count if the genome hat a total of 1000 mutations. This way, the MutSignatures analysis will be less biased toward the hyper-mutator samples.

Usage

frequencize(countMatrix, permille = TRUE)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

list including colSums (mutation burden of each sample) and freqs (matrix of frequencies)

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Examples

A <- cbind(c(7, 100, 90, 1000), c(1, 3, 5, 9))
fA <- mutSignatures::frequencize(A)
fA$freqs
 

Obtain COSMIC mutational Signatures.

Description

Obtain latest mutational Signature definitions from COSMIC. FOr more info, please visit: https://cancer.sanger.ac.uk/cosmic/

Usage

getCosmicSignatures(forceUseMirror = FALSE, asMutSign = TRUE)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

an object storing COSMIC mutational signature data

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Method getCounts.

Description

Retrieve mutation counts from an object.

Usage

getCounts(x)

## S4 method for signature 'mutationCounts'
getCounts(x)

Arguments

Method getFwkParam.

Description

Retrieve the list of parameters used for running a Mutation Signature Analysis.

Usage

getFwkParam(x, label)

## S4 method for signature 'mutFrameworkParams,character'
getFwkParam(x, label)

Arguments

Method getMutationTypes.

Description

Retrieve the list of mutation types from an object.

Usage

getMutationTypes(x)

## S4 method for signature 'mutationSignatures'
getMutationTypes(x)

## S4 method for signature 'mutationCounts'
getMutationTypes(x)

Arguments

Method getSampleIdentifiers.

Description

Retrieve the list of sample identifiers from an object.

Usage

getSampleIdentifiers(x)

## S4 method for signature 'mutationCounts'
getSampleIdentifiers(x = "mutationCounts")

## S4 method for signature 'mutSignExposures'
getSampleIdentifiers(x)

Arguments

Method getSignatureIdentifiers.

Description

Retrieve the list of signature identifiers from an object.

Usage

getSignatureIdentifiers(x)

## S4 method for signature 'mutSignExposures'
getSignatureIdentifiers(x)

## S4 method for signature 'mutationSignatures'
getSignatureIdentifiers(x)

Arguments

Generate Arguments for Running Examples and Mock Runs.

Description

This function generates objects that can be used for running the examples included in the package documentation files, as well as some simple mutSignature analyses. Note that his function is not exported.

Usage

getTestRunArgs(testN = "evaluateStability")

Arguments

Details

This is an internal function.

Value

an object (typically, a list) including sample data to run analyses or to test mutSignatures functions.

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. WTSI framework: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3588146/

Import Mutation data from VCF files.

Description

Import Mutation data from VCF files. The columns are expected in the following order: c("CHROM", "POS", "ID", "REF", "ALT", "QUAL", "FILTER", "INFO", "FORMAT"). Optional columns can be present to inform about sample ID or other info.

Usage

importVCFfiles(vcfFiles, sampleNames = NULL)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

a concatenated data.frame with all variants found in the input VCF files. Sample ID is stored in the "SAMPLEID" column.

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Add Leading Zeros to Numbers.

Description

Internal function to convert a numeric vector into a character vector, where all elements have the same number of characters (nchar). This is obtained by pasting a series of leading zeros (or other character) to each number in the input vector.

Usage

leadZeros(n, m, char = "0", na.value = NA)

Arguments

Details

This is one of the core functions included in the original mutSignatures R library, and in the WTSI MATLAB framework. This is an internal function.

Value

numeric vector of length equal to length(n), where all numbers are converted to character and modified by attaching the required number of leading zeros (characters).

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. WTSI framework: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3588146/

Examples

n = c(5:12, NA, 9:11)
m = 111
mutSignatures:::leadZeros(n=n, m=m)    

Match Mutational Signatures.

Description

Analyze the similarity between mutational signatures from different analyses/runs. THis function can be helpful to match de novo extracted signatures with previously described signatures (such as COSMIC), or to reveal signatures that can be identified with alternative NMF algorithms, or that may be due to an algorithm bias.

Usage

matchSignatures(
  mutSign,
  reference = NULL,
  method = "cosine",
  threshold = 0.5,
  plot = "TRUE"
)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

list, including distance matrix and a heatmap plot

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Method msigPlot.

Description

Generate standard plots using data from mutsignature-class objects.

Usage

msigPlot(x, ...)

## S4 method for signature 'mutationSignatures'
msigPlot(x, ...)

## S4 method for signature 'mutationCounts'
msigPlot(x, ...)

## S4 method for signature 'mutSignExposures'
msigPlot(x, ...)

Arguments

Class mutFrameworkParams.

Description

Class mutFrameworkParams defines objects including the set of parameters used for running a Mutational Signature Analysis.

Usage

## S4 method for signature 'mutFrameworkParams'
initialize(.Object, params)

Arguments

Slots

params

list including the set of parameters used for running a Mutational Signature Analysis

Author(s)

Damiano Fantini damiano.fantini@gmail.com

Input Data and Examples for Running Mutational Signatures Analyses

Description

A series of objects, including collections of DNA mutations from 50 Bladder cancer samples, as well as mutational signatures extracted from the same samples. Mutation catalogs were obtained from a TCGA bladder cancer dataset (data available from the BROAD Institute). Original sample IDs were shuffled and then re-encoded. Data are available in different formats, and can be used as input for running mutational signature analyses.

Usage

data("mutSigData")

Format

A list with 6 elements. Each element is a different type of mutSignatures input/data:

inputA

data.frame with 10401 rows and 4 columns. DNA mutation data mimicking a TCGA dataset downloaded using TCGAretriever/cBio

inputB

data.frame with 13523 rows and 12 columns. DNA mutation data mimicking a TCGA MAF file

inputC

data.frame with 13523 rows and 11 columns. DNA mutation data mimicking a VCF file decorated with a SAMPLEID column

inputC.ctx

data.frame with 13523 rows and 11 columns. DNA mutation data mimicking a VCF file decorated with a SAMPLEID column

inputD

data.frame with 13487 rows and 56 columns. DNA mutation data mimicking a set of VCF files casted into a 2D matrix (samples as columns)

inputS

list including data for silhouette plot generation (used in the vignette)

blcaMUTS

data.frame with 96 rows and 50 columns. A table of DNA mutation counts (rows are mutation types; columns are samples)

blcaSIGS

data.frame with 96 rows and 8 columns. Set of 8 mutational signatures (rows are mutation types; columns are signatures)

.addON

list of add-on functions (executed only upon request, not evaluated; these may require manual installation of external libraries from Bioconductor or GitHUB)

Details

Examples and more information are available in the vignette, as well as at the following URL: https://www.data-pulse.com/dev_site/mutsignatures/

Source

BLCA data were downloaded from http://gdac.broadinstitute.org/ and then further processed, modified, and formatted.

Examples

data(mutSigData)
print(mutSigData$input.A[1:6,])

Class mutSignExposures.

Description

Class mutSignExposures defines objects storing information about Exposures of biological samples to Mutational Signatures.

Usage

## S4 method for signature 'mutSignExposures'
initialize(.Object, x, samples, signNames)

Arguments

Slots

exposures

data.frame including information about exposures

sampleId

data.frame including information about sample identifiers

signatureId

data.frame including information about signature identifiers

Author(s)

Damiano Fantini damiano.fantini@gmail.com

Class mutationCounts.

Description

Class mutationCounts defines objects storing Mutation COunts data.

Usage

## S4 method for signature 'mutationCounts'
initialize(.Object, x, muts, samples)

Arguments

Slots

counts

data.frame including information about mutation counts

mutTypes

data.frame including information about mutation types

sampleId

data.frame including information about sample identifiers

Author(s)

Damiano Fantini damiano.fantini@gmail.com

Class mutationSignatures.

Description

Class mutationSignatures defines objects storing Mutational Signatures data.

Usage

## S4 method for signature 'mutationSignatures'
initialize(.Object, x, muts, signNames)

Arguments

Slots

mutationFreq

data.frame including information about mutation frequencies

mutTypes

data.frame including information about mutation types

signatureId

data.frame including information about mutation signature Identifiers

Author(s)

Damiano Fantini damiano.fantini@gmail.com

Plot Mutation Signature Profiles.

Description

Build a barplot to visualize the relative abundance of mutation counts in a mutational signature or biological sample of interest.

Usage

plotMutTypeProfile(
  mutCounts,
  mutLabs,
  freq = TRUE,
  ylim = "auto",
  ylab = "Fraction of Variants",
  xlab = "Sequence Motifs",
  xaxis_cex = 0.475,
  cols = c("#4eb3d3", "#040404", "#b30000", "#bdbdbd", "#41ab5d", "#dd3497"),
  main = "MutType Profile"
)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

NULL. A plot is printed to the active device.

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Plot Signature Exposure Profiles.

Description

Build a barplot to visualize exposures to mutation signatures.

Usage

plotSignExposures(mutCount, top = 50)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

a plot (ggplot2 object)

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

2. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

Run a Preliminary Process Assess analysis.

Description

This function is an attempt to analyze the relationship between error and k. In other words, the goal of prelimProcessAssess is to visualize the reduction in the error/residuals

Usage

prelimProcessAssess(
  input,
  maxProcess = 6,
  approach = "counts",
  plot = TRUE,
  verbose = TRUE
)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

a data.frame showing the estimated total error with respect to the range of k values

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Process VCF data.

Description

Check, annotate, and process variants imported from a list of VCF files, so that it can be used to run a mutational signature analysis

Usage

processVCFdata(
  vcfData,
  BSGenomeDb,
  chr_colName = "CHROM",
  pos_colName = "POS",
  ref_colName = "REF",
  alt_colName = "ALT",
  sample_colName = NULL,
  nucl_contextN = 3,
  verbose = TRUE
)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

a data.frame including processed variants from VCF files

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Remove Mismatched Mutations.

Description

Remove mutation types that do not match the expected nucleotidic context.

Usage

removeMismatchMut(
  mutData,
  refMut_colName = "mutation",
  context_colName = "context",
  refMut_format = "N>N"
)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

filtered data.frame

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Examples

x <- mutSignatures:::getTestRunArgs("removeMismatchMut")
y <- mutSignatures:::removeMismatchMut(x, 
                                       refMut_colName = "REF", 
                                       context_colName = "context", 
                                       refMut_format = "N")
y

Remove Mutation Types Not Meeting the Threshold.

Description

Remove mutation types that account for a total number of mutations below a defined threshold.

Usage

removeWeak(input_mutCounts, params)

Arguments

Details

This is one of the core functions included in the original mutSignatures R library, and in the WTSI MATLAB framework. This is an internal function.

Value

List including two elements:

1. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

2. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. WTSI framework: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3588146/

Examples

x <- mutSignatures:::getTestRunArgs("removeWeak")
nrow(x$data)
y <- mutSignatures:::removeWeak(input_mutCounts = x$data, params = x$params)
nrow(y)
  

Resolve Mutation Signatures.

Description

If Mutation signatures are known (such as COSMIC signatures), we can estimate the contribution of each signature in different samples. This functions used a matrix of mutation counts and a matrix of mutation signatures, and estimates Exposures to Mutational Signature of each sample.

Usage

resolveMutSignatures(mutCountData, signFreqData, byFreq = TRUE)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

a list of objects including data about exposures to mutational signatures

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Examples

    x <- mutSignatures:::getTestRunArgs("resolveMutSignatures")
    y <- mutSignatures::resolveMutSignatures(mutCountData = x$muts, signFreqData = x$sigs)
    y

Compute Reverse Complement sequences.

Description

Transform a DNA sequence into its reverse-complement sequence. ALternatively, only the reverse sequence (or only the complement) can be returned.

Usage

revCompl(DNAseq, rev = TRUE, compl = TRUE)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

a character vector including transformed DNA sequences

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Examples

A <- c("TAACCG", "CTCGA", "CNNA")
mutSignatures::revCompl(A)

Method setFwkParam.

Description

Set or update one of the parameters in a mutFrameworkParams-class object. Individual paramaters can be set or updated, by passing the parameter label, and the corresponding parameter value.

Usage

setFwkParam(x, label, value)

## S4 method for signature 'mutFrameworkParams,character'
setFwkParam(x, label, value)

Arguments

Set Parameters for Extracting Mutational Signatures.

Description

Create an object including all parameters required for running the mutSignatures framework.

Usage

setMutClusterParams(
  num_processesToExtract = 2,
  num_totIterations = 10,
  num_parallelCores = 1,
  thresh_removeWeakMutTypes = 0.01,
  thresh_removeLastPercent = 0.07,
  distanceFunction = "cosine",
  num_totReplicates = 100,
  eps = 2.2204e-16,
  stopconv = 20000,
  niter = 1e+06,
  guided = TRUE,
  debug = FALSE,
  approach = "freq",
  stopRule = "DF",
  algorithm = "brunet",
  logIterations = "lite",
  seed = 12345
)

Arguments

Value

Object including all parameters for running the analysis

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. WTSI framework: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3588146/

Examples

library(mutSignatures) 
# defaults params
A <- setMutClusterParams()
A
# A second example, set num_processes
B <- setMutClusterParams(num_processesToExtract = 5)
B

    

Show method of the mutFrameworkParams Class.

Description

Show method of the mutFrameworkParams Class.

Print method of the mutFrameworkParams Class.

Usage

## S4 method for signature 'mutFrameworkParams'
show(object)

## S4 method for signature 'mutFrameworkParams'
print(x)

Arguments

Show method of the mutSignExposures Class.

Description

Show method of the mutSignExposures Class.

Print method of the mutSignExposures Class.

Usage

## S4 method for signature 'mutSignExposures'
show(object)

## S4 method for signature 'mutSignExposures'
print(x)

Arguments

Show method of the mutationCounts Class.

Description

Show method of the mutationCounts Class.

Print method of the mutationCounts Class.

Usage

## S4 method for signature 'mutationCounts'
show(object)

## S4 method for signature 'mutationCounts'
print(x)

Arguments

Show method of the mutationSignatures Class.

Description

Show method of the mutationSignatures Class.

Print method of the mutationSignatures Class.

Usage

## S4 method for signature 'mutationSignatures'
show(object)

## S4 method for signature 'mutationSignatures'
print(x)

Arguments

Silhouette Analysis.

Description

Analyze the clustering quality and generate a Silhouette Plot.

Usage

silhouetteMLB(data, fac, method = "cosine", plot = TRUE)

Arguments

Value

numeric vector including the silhouette values of the data poointts in the input matrix

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

5. Silhouette analysis in R: http://www.biotechworld.it/bioinf/2017/01/20/translating-matlabs-silhouette-function-to-r/

Examples

library(mutSignatures)
x <- mutSignatures:::getTestRunArgs("silhouetteMLB")
y <- silhouetteMLB(data = x$data, fac = x$fac)
y

Simplify Mutational Signatures.

Description

This function is useufl when working with non-standard muation types, such as tetra-nnucleotide mutation types or mutation types with long/complex context. THe goal of this function is to aggregated together mutations that can be simplified because of a common mutation core. For example, mutation types AA[A>T]A, TA[A>T]A, CA[A>T]A, and GA[A>T]A can be simplified to the core tri-nucleotide mutation A[A>T]A. THis function identifies mergeable mutation types, and aggregates the corresponding counts/freqs.

Usage

simplifySignatures(x, asMutationSignatures = TRUE)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

object including simplified mutational signatures data

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Examples

A <- data.frame(Sig1=1:5, Sig2=5:1, Sig3=1:5)
A <- A/apply(A, 2, sum)
rownames(A) <- c("AA[C>A]A", "CA[C>A]A", "TA[C>A]A", "TA[C>G]A", "A[C>G]AT")
A <- mutSignatures::as.mutation.signatures(A)
mutSignatures::simplifySignatures(x = A)

Sort Data by Mutation Type.

Description

Reorder a mutationSignatures, mutationCounts, data.frame, or matrix object by sorting entries by mutation type.

Usage

sortByMutations(x)

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

an object of the same class as x, with entries sorted according to mutation types.

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. GitHub Repo: https://github.com/dami82/mutSignatures/

2. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

3. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

4. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Examples

A <- data.frame(S1=1:5, S2=5:1, S3=1:5)
rownames(A) <- c("A[A>T]G", "A[C>G]G", "T[A>T]G", "T[C>G]T", "T[C>G]G")
mutSignatures::sortByMutations(A)

Table Mutation Types by Sample.

Description

Prepare a molten data.frame starting from a mutation count matrix. Mutation types (rows) are countes for each sample (cols). The results are returned in a 3-column data.frame.

Usage

table2df(dataMatrix, rowLab = "sample", colLab = "feature", valueLab = "count")

Arguments

Details

This function is part of the user-interface set of tools included in mutSignatures. This is an exported function.

Value

data.frame storing mutation counts by sample

Author(s)

Damiano Fantini, damiano.fantini@gmail.com

References

More information and examples about mutational signature analysis can be found here:

1. More info and examples about the mutSignatures R library: https://www.data-pulse.com/dev_site/mutsignatures/

2. Sci Rep paper, introducing mutS: https://www.nature.com/articles/s41598-020-75062-0/

3. Oncogene paper, Mutational Signatures Operative in Bladder Cancer: https://www.nature.com/articles/s41388-017-0099-6

Examples

A <- cbind(`A>G`=c(5,10),`A>T`=c(3,20),`A>C`=c(15,0))
rownames(A) = c("Smpl1", "Smpl2")
mutSignatures::table2df(A)