run_SMC {YAPSA} | R Documentation

## Wrapper function for the Stratification of a Mutational Catalogue

### Description

`run_SMC` takes as input a big dataframe constructed from a vcf-like file of a whole cohort. This wrapper function calls custom functions to construct a mutational catalogue and stratify it according to categories indicated by a special column in the input dataframe:

- `create_mutation_catalogue_from_df`

- `adjust_number_of_columns_in_list_of_catalogues`

This stratification yields a collection of stratified mutational catalogues, these are reformatted and sent to the custom function `SMC` and thus indirectly to `LCD_SMC` to perform a signature analysis of the stratified mutational catalogues. The result is then handed over to `plot_SMC` for visualization.

### Usage

    run_SMC(
      my_table,
      this_signatures_df,
      this_signatures_ind_df,
      this_subgroups_df,
      column_name,
      refGenome,
      cohort_method_flag = "all_PIDs",
      in_strata_order_ind = seq_len(length(unique(my_table[, column_name]))),
      wordLength = 3,
      verbose_flag = 1,
      target_dir = NULL,
      strata_dir = NULL,
      output_path = NULL,
      in_all_exposures_df = NULL,
      in_rownames = c(),
      in_norms = NULL,
      in_label_orientation = "turn",
      this_sum_ind = NULL
    )

### Arguments

`my_table` | A big dataframe constructed from a vcf-like file of a whole cohort. The first columns are those of a standard vcf file, followed by an arbitrary number of custom or user defined columns. One of these must carry a PID (patient or sample identifyier) and one must be the category used for stratification.
`this_signatures_df` | A numeric data frame `W` in with `n` rows and `l` columns, `n` being the number of features and `l` being the number of signatures
`this_signatures_ind_df` | A data frame containing meta information about the signatures
`this_subgroups_df` | A data frame indicating which PID (patient or sample identifyier) belongs to which subgroup
`column_name` | Name of the column in `my_table` which is going to be used for stratification
`refGenome` | FaFile of the reference genome to extract the motif context of the variants in `my_table`
`cohort_method_flag` | Either or several of `c("all_PIDs","cohort","norm_PIDs")`, representing alternative ways to average over the cohort.
`in_strata_order_ind` | Index vector defining reordering of the strata
`wordLength` | Integer number defining the length of the features or motifs, e.g. 3 for tripletts or 5 for pentamers
`verbose_flag` | Verbose if `verbose_flag=1`
`target_dir` | Path to directory where the results of the stratification procedure are going to be stored if non-NULL.
`strata_dir` | Path to directory where the mutational catalogues of the different strata are going to be stored if non-NULL
`output_path` | Path to directory where the results, especially the figures produced by `plot_SMC` are going to be stored.
`in_all_exposures_df` | Optional argument, if specified, `H`, i.e. the overall exposures without stratification, is set to equal `in_all_exposures_df`. This is equivalent to forcing the `LCD_SMC` procedure to use e.g. the exposures of a previously performed NMF decomposition.
`in_rownames` | Optional parameter to specify rownames of the mutational catalogue `V` i.e. the names of the features.
`in_norms` | If specified, vector of the correction factors for every motif due to differing trinucleotide content. If null, no correction is applied.
`in_label_orientation` | Whether or not to turn the labels on the x-axis.
`this_sum_ind` | Optional set of indices for reordering the PIDs

### Value

A list with entries `exposures_list`, `catalogues_list`, `cohort` and `name_list`.

- `exposures_list`: The list of `s` strata specific exposures Hi, all are numerical data frames with `l` rows and `m` columns, `l` being the number of signatures and `m` being the number of samples

- `catalogues_list`: A list of `s` strata specific cohortwide (i.e. averaged over cohort) normalized exposures

- `cohort`: `subgroups_df` adjusted for plotting

- `name_list`: Names of the contructed strata.

### See Also

`create_mutation_catalogue_from_df`

`normalizeMotifs_otherRownames`

`plot_SMC`

### Examples

     library(BSgenome.Hsapiens.UCSC.hg19)
     data(sigs)
     data(lymphoma_test)
     data(lymphoma_cohort_LCD_results)
     strata_list <-
       cut_breaks_as_intervals(lymphoma_test_df$random_norm,
                               in_outlier_cutoffs=c(-4,4),
                               in_cutoff_ranges_list=list(c(-2.5,-1.5),
                                                          c(0.5,1.5)),
                               in_labels=c("small","intermediate","big"))
     lymphoma_test_df$random_cat <- strata_list$category_vector
     choice_ind <- (names(lymphoma_Nature2013_COSMIC_cutoff_exposures_df)
                    %in% unique(lymphoma_test_df$PID))
     lymphoma_test_exposures_df <-
       lymphoma_Nature2013_COSMIC_cutoff_exposures_df[,choice_ind]
     temp_subgroups_df <- make_subgroups_df(lymphoma_test_df,
                                            lymphoma_test_exposures_df)
     mut_density_list <- run_SMC(lymphoma_test_df,
                                 AlexCosmicValid_sig_df,
                                 AlexCosmicValid_sigInd_df,
                                 temp_subgroups_df,
                                 column_name="random_cat",
                                 refGenome=BSgenome.Hsapiens.UCSC.hg19,
                                 cohort_method_flag="norm_PIDs",
                                 in_rownames = rownames(AlexCosmicValid_sig_df))

[Package YAPSA version 1.18.0 Index]