strand_bias_test {MutationalPatterns} | R Documentation

## Significance test for strand asymmetry

### Description

This function performs a two sided Poisson test for the ratio between mutations on each strand. Multiple testing correction is also performed.

### Usage

    strand_bias_test(strand_occurrences, p_cutoffs = 0.05, fdr_cutoffs = 0.1)

### Arguments

`strand_occurrences` | Dataframe with mutation count per strand, result from 'strand_occurrences()'
`p_cutoffs` | Significance cutoff for the p value. Default: 0.05
`fdr_cutoffs` | Significance cutoff for the fdr. Default: 0.1

### Value

Dataframe with poisson test P value for the ratio between the two strands per group per base substitution type.

### See Also

`mut_matrix_stranded`, `strand_occurrences`, `plot_strand_bias`

### Examples

    ## See the 'mut_matrix_stranded()' example for how we obtained the
    ## following mutation matrix.
    mut_mat_s <- readRDS(system.file("states/mut_mat_s_data.rds",
      package = "MutationalPatterns"
    ))

    tissue <- c(
      "colon", "colon", "colon",
      "intestine", "intestine", "intestine",
      "liver", "liver", "liver"
    )

    ## Perform the strand bias test.
    strand_counts <- strand_occurrences(mut_mat_s, by = tissue)
    strand_bias <- strand_bias_test(strand_counts)

    ## Use different significance cutoffs for the pvalue and fdr
    strand_bias_strict <- strand_bias_test(strand_counts,
      p_cutoffs = 0.01, fdr_cutoffs = 0.05
    )

    ## Use multiple (max 3) significance cutoffs.
    ## This will vary the number of significance stars.
    strand_bias_multistars <- strand_bias_test(strand_counts,
      p_cutoffs = c(0.05, 0.01, 0.005),
      fdr_cutoffs = c(0.1, 0.05, 0.01)
    )

[Package MutationalPatterns version 3.0.1 Index]