LCD_complex_cutoff: LCD with a signature-specific cutoff on exposures

Description Usage Arguments Value See Also Examples

View source: R/LCD.R

Description

LCD_cutoff performs a mutational signatures decomposition by Linear Combination Decomposition (LCD) of a given mutational catalogue V with known signatures W by solving the minimization problem min(||W*H - V||) with additional constraints of non-negativity on H where W and V are known, but excludes signatures with an overall contribution less than a given signature-specific cutoff (and thereby accounting for a background model) over the whole cohort.

LCD_complex_cutoff_perPID is a wrapper for LCD_complex_cutoff and runs individually for every PID.

LCD_complex_cutoff_consensus calls LCD_complex_cutoff_combined AND LCD_complex_cutoff_perPID and makes a consensus signature call set.

LCD_complex_cutoff_combined is a wrapper for LCD_complex_cutoff, LCD_complex_cutoff_perPID AND LCD_complex_cutoff_consensus.

Usage

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LCD_complex_cutoff(
  in_mutation_catalogue_df,
  in_signatures_df,
  in_cutoff_vector = NULL,
  in_filename = NULL,
  in_method = "abs",
  in_per_sample_cutoff = 0,
  in_rescale = TRUE,
  in_sig_ind_df = NULL,
  in_cat_list = NULL
)

LCD_complex_cutoff_perPID(
  in_mutation_catalogue_df,
  in_signatures_df,
  in_cutoff_vector = NULL,
  in_filename = NULL,
  in_method = "abs",
  in_rescale = TRUE,
  in_sig_ind_df = NULL,
  in_cat_list = NULL
)

LCD_complex_cutoff_consensus(
  in_mutation_catalogue_df = NULL,
  in_signatures_df = NULL,
  in_cutoff_vector = NULL,
  in_filename = NULL,
  in_method = "abs",
  in_rescale = TRUE,
  in_sig_ind_df = NULL,
  in_cat_list = NULL,
  in_cohort_LCDlist = NULL,
  in_perPID_LCDlist = NULL,
  addSigs_cohort_cutoff = 0.25,
  addSigs_perPID_cutoff = 0.25,
  addSigs_relAbs_cutoff = 0.01,
  keep.unassigned = FALSE,
  keep.all.cohort.sigs = TRUE,
  in_verbose = FALSE
)

LCD_complex_cutoff_combined(
  in_mutation_catalogue_df = NULL,
  in_signatures_df = NULL,
  in_cutoff_vector = NULL,
  in_filename = NULL,
  in_method = "abs",
  in_rescale = TRUE,
  in_sig_ind_df = NULL,
  in_cat_list = NULL,
  addSigs_cohort_cutoff = 0.25,
  addSigs_perPID_cutoff = 0.25,
  addSigs_relAbs_cutoff = 0.01,
  keep.all.cohort.sigs = TRUE,
  in_verbose = FALSE
)

Arguments

in_mutation_catalogue_df

A numeric data frame V with n rows and m columns, n being the number of features and m being the number of samples

in_signatures_df

A numeric data frame W with n rows and l columns, n being the number of features and l being the number of signatures

in_cutoff_vector

A numeric vector of values less than 1. Signatures from within W with an overall exposure less than the respective value in in_cutoff_vector will be discarded.

in_filename

A path to generate a histogram of the signature exposures if non-NULL

in_method

Indicate to which data the cutoff shall be applied: absolute exposures, relative exposures

in_per_sample_cutoff

A numeric value less than 1. Signatures from within W with an exposure per sample less than in_cutoff will be discarded.

in_rescale

Boolean, if TRUE (default) the exposures are rescaled such that colSums over exposures match colSums over mutational catalogue

in_sig_ind_df

Data frame of type signature_indices_df, i.e. indicating name, function and meta-information of the signatures. Default is NULL.

in_cat_list

List of categories for aggregation. Have to be among the column names of in_sig_ind_df. Default is NULL.

in_cohort_LCDlist

Optional, if not provided, the cohort-wide exposures are recalculated by calling LCD_complex_cutoff

in_perPID_LCDlist

Optional, if not provided, the per sample exposures are recalculated by calling LCD_complex_cutoff_perPID

addSigs_cohort_cutoff

Numeric value for a cutoff: signatures which are detected in a fraction of the samples of the cohort greater than this cutoff are kept for the consensus set of signatures

addSigs_perPID_cutoff

Numeric value for a cutoff: signatures which are detected in one sample with exposure greater than this cutoff are kept for the consensus set of signatures

addSigs_relAbs_cutoff

Numeric value for a cutoff: signatures which are detected with at least this fraction of all variants cohort wide are kept for the consensus set of signatures

keep.unassigned

Boolean, if TRUE the exposures from the signatures which don't fulfill the criteria to be kept will be added and stored in the exposures as "unassigned", otherwise the exposures are rescaled.

keep.all.cohort.sigs

If TRUE (default), all signatures extracted cohort wide are kept, if FALSE, the function reevaluates whether the signatures extracted cohort wide still fulfill their criteria (i.e. exposures > cutoff) after perPID extraction.

in_verbose

Verbose if in_verbose=1

Value

A list with entries:

See Also

LCD

aggregate_exposures_by_category

lsei

Examples

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slw287r/yapsa documentation built on June 7, 2020, 12:46 a.m.