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Heritability and variance components table

Source: R/tbl_heritability.R
tbl_heritability.Rd

Formats a tidy data frame of narrow-sense heritability estimates (h2) into a publication-ready table. Column-name defaults match the output of R-itable::herit_batch() directly.

Column-name arguments accept character strings (quoted names).

Usage

tbl_heritability(
  data,
  metric = "trait",
  h2 = "h2",
  ci_low = "ci_lo",
  ci_high = "ci_hi",
  p = "pval",
  sigma2_a = NULL,
  sigma2_e = NULL,
  model = NULL,
  domains = list(),
  fdr = FALSE,
  fdr_within = NULL,
  digits = 2,
  p_digits = 3,
  output = c("gt", "html", "latex")
)

Arguments

data

A tidy data frame with one row per trait x covariate model.

metric

Character string. Name of the trait/phenotype column. Default "trait" (matches herit_batch()).

h2

Character string. Name of the h2 estimate column. Default "h2".

ci_low

Character string. Name of the lower 95% CI bound column. Default "ci_lo" (matches herit_batch()).

ci_high

Character string. Name of the upper 95% CI bound column. Default "ci_hi" (matches herit_batch()).

p

Character string. Name of the one-sided LRT p-value column. Default "pval" (matches herit_batch()).

sigma2_a

Character string or NULL. Name of the additive genetic variance column. Default NULL.

sigma2_e

Character string or NULL. Name of the residual variance column. Default NULL.

model

Character string or NULL. Name of a column identifying covariate models. Pass "covariates" when using herit_batch() output. Default NULL.

domains

A named list mapping trait names to domain/section labels.

fdr

Logical. Apply BH FDR correction (default FALSE).

fdr_within

Character string or NULL. Column name to group FDR correction within.

digits

Integer. Decimal places for h2 and variance components (default 2).

p_digits

Integer. Decimal places for p-values (default 3).

output

Character string. One of "gt" (default), "html", or "latex".

Value

A clerk_tbl object with type "heritability".

Examples

tbl_heritability(
  clerk_h2_example,
  model    = "covariates",
  sigma2_a = "sigma2_a",
  sigma2_e = "sigma2_e",
  fdr      = TRUE,
  output   = "gt"
) |> clerk_render(title = "Heritability estimates for cortical shape metrics")



  
Heritability estimates for cortical shape metrics
    

      covariates
      h²
      95% CI
      p
      σ²a
      σ²e
      p (FDR)
    
All variables
    
K (tension)
unadj
0.48
[0.28, 0.70]
<0.001
0.31
0.34
<0.001
S (shape)
unadj
0.73
[0.57, 0.88]
<0.001
0.47
0.18
<0.001
I (isometric)
unadj
0.45
[0.27, 0.64]
<0.001
0.29
0.36
<0.001
K (tension)
cov1
0.61
[0.45, 0.79]
<0.001
0.40
0.25
<0.001
S (shape)
cov1
0.81
[0.62, 1.00]
<0.001
0.53
0.12
<0.001
I (isometric)
cov1
0.69
[0.54, 0.87]
<0.001
0.45
0.20
<0.001
K (tension)
cov2
0.62
[0.40, 0.82]
<0.001
0.40
0.25
<0.001
S (shape)
cov2
0.84
[0.67, 1.00]
<0.001
0.55
0.10
<0.001
I (isometric)
cov2
0.67
[0.48, 0.83]
<0.001
0.44
0.21
<0.001
K (tension)
cov3
0.63
[0.46, 0.79]
<0.001
0.41
0.24
<0.001
S (shape)
cov3
0.81
[0.59, 0.99]
<0.001
0.53
0.12
<0.001
I (isometric)
cov3
0.67
[0.46, 0.88]
<0.001
0.44
0.21
<0.001