standardize: Standardize Allelic Ratio Data and Compute BAF and Z-Scores

In Qploidy: Estimation of Ploidy and Detection of Aneuploidy Using Genotyping Data

Standardize Allelic Ratio Data and Compute BAF and Z-Scores

Description

This function performs signal standardization of genotype data by aligning 'theta' values (allelic ratios or normalized intensities) to expected genotype clusters. It outputs standardized BAF (B-allele frequency) and Z-scores per sample and marker.

Usage

standardize(
  data = NULL,
  genos = NULL,
  geno.pos = NULL,
  threshold.missing.geno = 0.9,
  threshold.geno.prob = 0.8,
  ploidy.standardization = NULL,
  threshold.n.clusters = NULL,
  n.cores = 1,
  out_filename = NULL,
  type = "intensities",
  multidog_obj = NULL,
  parallel.type = "PSOCK",
  verbose = TRUE,
  rm_outlier = TRUE,
  cluster_median = TRUE
)

Arguments

data	A 'data.frame' containing the full dataset with the following columns: - MarkerName: Marker identifiers. - SampleName: Sample identifiers. - X: Reference allele intensity or count. - Y: Alternative allele intensity or count. - R: Total signal intensity or read depth (X + Y). - ratio: Allelic ratio, typically Y / (X + Y).
genos	A 'data.frame' containing genotype dosage information for the reference panel. - MarkerName: Marker identifiers. - SampleName: Sample identifiers. - geno: Estimated dosage (0, 1, 2, ...). - prob: Genotype call probability (used for filtering low-confidence genotypes).
geno.pos	A 'data.frame' with marker position metadata. - MarkerName: Marker identifiers. - Chromosome: Chromosome names. - Position: Base-pair positions on the genome.
threshold.missing.geno	Numeric (0–1). Maximum fraction of missing genotype data allowed per marker. Markers with a higher fraction will be removed.
threshold.geno.prob	Numeric (0–1). Minimum genotype call probability threshold. Genotypes with lower probability will be treated as missing.
ploidy.standardization	Integer. The ploidy level of the reference panel used for standardization.
threshold.n.clusters	Integer. Minimum number of expected dosage clusters per marker. For diploid data, this is typically 3 (corresponding to genotypes 0, 1, and 2).
n.cores	Integer. Number of cores to use in parallel computations (e.g., for cluster center estimation and BAF generation).
out_filename	Optional. Path to save the final standardized dataset to disk as a CSV file (suitable for Qploidy).
type	Character. Type of data used for clustering: - "intensities": For array-based allele intensity data. - "counts": For sequencing data. - "updog": Automatically set when 'multidog_obj' is provided.
multidog_obj	Optional. An object of class 'multidog' from the 'updog' package, containing model fits and estimated biases. If provided, this will override the ‘type' parameter and use 'updog'’s expected cluster positions.
parallel.type	Character. Parallel backend to use ("FORK" or "PSOCK"). "FORK" is faster but only works on Unix-like systems.
verbose	Logical. If TRUE, prints progress and filtering information to the console.
rm_outlier	Logical. If TRUE, uses Bonferroni-Holm corrected residuals to remove outliers before estimating cluster centers.
cluster_median	Logical. If TRUE, uses the median of theta values to estimate cluster centers. If FALSE, uses the mean.

Details

Reference genotypes are used to estimate cluster centers either from dosage data (e.g., via 'fitpoly' or 'updog') or using an 'updog' 'multidog' object directly. This function supports both array-based (intensity) and sequencing-based (count) data.

It applies marker and genotype-level quality filters, uses parallel computing to estimate BAF, and generates a final annotated output suitable for CNV or dosage variation analyses.

Filtering steps: 1. Genotype probability filter: Genotypes with probability below 'threshold.geno.prob' are set to missing. 2. Marker missingness filter: Markers with fraction of missing genotypes above 'threshold.missing.geno' are removed. 3. Cluster number filter: Markers with fewer than 'threshold.n.clusters' clusters are removed. 4. Genomic info filter: Markers lacking chromosome or position info are removed.

Merging logic: - The function merges filtered genotype and signal data, estimates cluster centers, computes BAFs in parallel, and calculates Z-scores. Results are merged into a single output data.frame containing BAF, Z-score, and genotype info.

Value

An object of class "qploidy_standardization" (list) with the following components: - info: Named vector of standardization parameters. - filters: Named vector summarizing how many markers were removed at each filtering step. - data: A data.frame containing merged BAF, Z-score, and genotype information by marker and sample.

Qploidy documentation built on July 11, 2026, 5:06 p.m.