Skip to contents

Calculate Repeat Instability Metrics

calculate_instability_metrics.Rd

This function computes instability metrics from a list of fragments_repeats data objects.

Usage

calculate_instability_metrics(
  fragments_list,
  peak_threshold = 0.05,
  window_around_index_peak = c(NA, NA),
  percentile_range = c(0.5, 0.75, 0.9, 0.95),
  repeat_range = c(2, 5, 10, 20)
)

Arguments

fragments_list

A list of "fragments_repeats" objects representing fragment data.

peak_threshold

The threshold for peak signals to be considered in the calculations, relative to the modal peak signal of the expanded allele.

window_around_index_peak

A numeric vector (length = 2) defining the range around the index peak. First number specifies repeats before the index peak, second after. For example, c(-5, 40) around an index peak of 100 would analyze repeats 95 to 140. The sign of the numbers does not matter (The absolute value is found).

percentile_range

A numeric vector of percentiles to compute (e.g., c(0.5, 0.75, 0.9, 0.95)).

repeat_range

A numeric vector specifying ranges of repeats for the inverse quantile computation.

Value

A data.frame with calculated instability metrics for each sample.

Details

Each of the columns in the supplied dataframe are explained below:

General Information

  • unique_id: A unique identifier for the sample (usually the fsa file name).

Quality Control

  • QC_comments: Quality control comments.

  • QC_modal_peak_signal: Quality control status based on the modal peak signal (Low < 500, very low < 100).

  • QC_peak_number: Quality control status based on the number of peaks (Low < 20, very low < 10).

  • QC_off_scale: Quality control comments for off-scale peaks. Potential peaks that are off-scale are given. However, a caveat is that this could be from any of the channels (ie it could be from the ladder channel but is the same scan as the given repeat).

General sample metrics

  • modal_peak_repeat: The repeat size of the modal peak.

  • modal_peak_signal: The signal of the modal peak.

  • index_peak_repeat: The repeat size of the index peak (the repeat value closest to the modal peak of the index sample).

  • index_peak_signal: The signal of the index peak.

  • index_weighted_mean_repeat: The weighted mean repeat size (weighted on the signal of the peaks) of the index sample.

  • n_peaks_total: The total number of peaks in the repeat table.

  • n_peaks_analysis_subset: The number of peaks in the analysis subset.

  • n_peaks_analysis_subset_expansions: The number of expansion peaks in the analysis subset.

  • min_repeat: The minimum repeat size in the analysis subset.

  • max_repeat: The maximum repeat size in the analysis subset.

  • mean_repeat: The mean repeat size in the analysis subset.

  • weighted_mean_repeat: The weighted mean repeat size (weight on peak signal) in the analysis subset.

  • median_repeat: The median repeat size in the analysis subset.

  • max_signal: The maximum peak signal in the analysis subset.

  • max_delta_neg: The maximum negative delta to the index peak.

  • max_delta_pos: The maximum positive delta to the index peak.

  • skewness: The skewness of the repeat size distribution.

  • kurtosis: The kurtosis of the repeat size distribution.

Repeat instability metrics

  • modal_repeat_change: The difference between the modal repeat and the index repeat.

  • average_repeat_change: The weighted mean of the sample (weighted by peak signal) subtracted by the weighted mean repeat of the index sample(s).

  • instability_index_change: The instability index of the sample subtracted by the instability index of the index sample(s). This will be very similar to the average_repeat_change, with the key difference of instability_index_change being that it is an internally calculated metric for each sample, and therefore the random slight fluctuations of bp size (or systematic if across plates for example) will be removed. However, it requires the index peak to be correctly set for each sample, and if set incorrectly, can produce large arbitrary differences.

  • instability_index: The instability index based on peak signal and distance to the index peak. (See Lee et al., 2010, doi:10.1186/1752-0509-4-29 ).

  • instability_index_abs: The absolute instability index. The absolute value is taken for the "Change from the main allele".

  • expansion_index: The instability index for expansion peaks only.

  • contraction_index: The instability index for contraction peaks only.

  • expansion_ratio: The ratio of expansion peaks' signals to the main peak signal. Also known as "peak proportional sum" (See Genetic Modifiers of Huntington’s Disease (GeM-HD) Consortium, 2019, doi:10.1016/j.cell.2019.06.036 ).

  • contraction_ratio: The ratio of contraction peaks' signals to the main peak signal.

  • expansion_percentile_*: The repeat size at specified percentiles of the cumulative distribution of expansion peaks.

  • expansion_percentile_for_repeat_*: The percentile rank of specified repeat sizes in the distribution of expansion peaks.

Examples

gm_raw <- trace::example_data
metadata <- trace::metadata

test_fragments <- peak_table_to_fragments(gm_raw,
  data_format = "genemapper5",
  dye_channel = "B",
  min_size_bp = 400
)

add_metadata(
  fragments_list = test_fragments,
  metadata_data.frame = metadata
)

find_alleles(
  fragments_list = test_fragments,
  peak_region_size_gap_threshold = 6,
  peak_region_signal_threshold_multiplier = 1
)


call_repeats(
  fragments_list = test_fragments,
  assay_size_without_repeat = 87,
  repeat_size = 3
)

assign_index_peaks(
  fragments_list = test_fragments,
  grouped = TRUE
)


# grouped metrics
# uses t=0 samples as indicated in metadata
test_metrics_grouped <- calculate_instability_metrics(
  fragments_list = test_fragments,
  peak_threshold = 0.05,
  window_around_index_peak = c(-40, 40),
  percentile_range = c(0.5, 0.75, 0.9, 0.95),
  repeat_range = c(2, 5, 10, 20)
)