getSummaryPatterns: getSummaryPatterns

In AlexJanse/cMut: Identify Clustered Single Nucleotide Mutations and Link Them to Mutational Patterns

Description

A optional follow-up function to summarize the results of the foundPatterns column from groupClusters.

Usage

getSummaryPatterns(groupedClusters, searchPatterns = NULL,
  searchIdHeader = "process", renameReverse = FALSE, asTibble = TRUE)

Arguments

groupedClusters	A table generated from the groupClusters.
searchPatterns	A tibble with the known mutation patterns. The mutationPatterns is the default search table.
searchIdHeader	A string with the column name of the one with the pattern IDs.
renameReverse	A Boolean to tell if the pattern IDs from the searchPatterns also needs to be used to find the patterns with " [Rev.Com.]". If FALSE and those patterns are available, then they will be counted in the Unidentified row.
asTibble	A Boolean to tell if the returned table needs to be a tibble or a data.frame.

Note

If the groupedClusters table contains patterns that are not present in the searchPattern table, then they will be marked as Unidentified together with clusters without patterns.

Examples

# Example dataset
data <- testDataSet

# Use the following functions to get the necessary table
results <- identifyClusters(dataTable    = data,
                            maxDistance  = 20000,
                            linkPatterns = TRUE)
groupResults <- groupClusters(dataTable             = results,
                              searchClusterPatterns = TRUE,
                              patternIntersect      = TRUE)

# Use the getSummaryPatterns function to see the summary of found patterns
summary <- getSummaryPatterns(groupResults)
summary

# For more information about the columns use:
cat(comment(summary))

AlexJanse/cMut documentation built on May 25, 2019, 4 a.m.