Regress tAge on a continuous predictor — tage_regress

Slope of predicted tAge against a numeric predictor such as chronological age, dose or time in culture. Elastic net clocks use lm; Bayesian ridge clocks use a REML meta-regression weighted by the per-sample prediction standard deviation and report z-tests.

Usage

tage_regress_continuous(
  data,
  value_columns,
  predictor,
  covariates = NULL,
  split_by = NULL,
  se_columns = NULL,
  p_adjust = TAGE_P_ADJUST_METHODS,
  p_adjust_scope = c("within_column", "across_columns", "global", "none"),
  conf_level = 0.95
)

Arguments

data: Data frame of per-sample predictions.
value_columns: Character vector of tAge columns.
predictor: Numeric column regressed against.
covariates: Additional fixed-effect columns. Default NULL.
split_by: Column to stratify on. Default NULL.
se_columns: Per-sample standard-deviation columns for Bayesian ridge clocks; see tage_compare_groups.
p_adjust: Method passed to p.adjust.
p_adjust_scope: Correction family; see tage_compare_groups. Because there is one test per clock and stratum, "across_columns" corrects across clocks within a stratum.
conf_level: Two-sided confidence level for ci_low / ci_high.

Value

A data frame with value_column, split, term, n, estimate (slope per unit of predictor), se, ci_low, ci_high, statistic, df, p_value, p_adjusted and label.

Examples

if (FALSE) { # \dontrun{
tage_regress_continuous(
  results,
  value_columns = "scaled_diff_EN_tAge",
  predictor     = "age_months",
  split_by      = "Tissue"
)
} # }