detect_arm_overfragmentation: Determines arm-level over-fragmentation patterns.

In caravagnalab/CNAqc: CNAqc - Copy Number Analysis quality check

Determines arm-level over-fragmentation patterns.

Description

The fragmentation of a chromosome arm is assessed with a statistical test based on counting the size of the copy number segments mapping to the arm. This analysis works only at the level of clonal CNAs.

CNAqc counts, for every arm with lenght $L$ nucleotides:

- the number of mapped CNA segments shorter than a percentage of $L$; - the number of mapped CNA segments longer than a percentage of $L$.

A one-sided Binomial test is used to compute a p-value. In this way the test accounts for the difference in lenghts of the chromsome arms; a p-value per arm is reported and adjusted for multiple hyoptheses (Bonferroni).

Usage

detect_arm_overfragmentation(
  x,
  alpha = 0.01,
  genome_percentage_cutoff = 0.2,
  minimum_segments_for_testing = 10
)

Arguments

x	A CNAqc object.
alpha	Confidence level for the tests, for instance 0.05.
genome_percentage_cutoff	Segments are considered long or short depending on whether they are longer (in basepairs) than genome_percentage_cutoff * L bases, where L is the arm length for the reference genome. Default is 0.2 (twenty percent).
minimum_segments_for_testing	Smallest number of segments required to actually test a certain arm Default is 10 segments. This number influences the correction for mulitple hypothesis testing.

Value

A CNAqc objectwith the results.

Examples

data('example_dataset_CNAqc')
x = init(mutations = example_dataset_CNAqc$mutations, cna = example_dataset_CNAqc$cna, purity = example_dataset_CNAqc$purity)

x = detect_arm_overfragmentation(x)

# Report to console
print(x)

caravagnalab/CNAqc documentation built on Oct. 31, 2024, 3:54 a.m.