Compute relative odds ratio at isodecoder level.

Compare isodecoder-level odds ratios between two conditions by computing the relative odds ratio (ROR) with z-score significance testing.

Usage

compute_ror_isodecoder(
  data_num,
  data_den,
  ror_cap = 10,
  p_method = "BH",
  alpha = 0.05
)

Arguments

data_num

A tibble of isodecoder-aggregated odds ratios for the numerator condition (from aggregate_or_isodecoder()).

data_den

A tibble of isodecoder-aggregated odds ratios for the denominator condition.

ror_cap

Maximum absolute value for the ROR. Values beyond this are capped. Default 10.

p_method

Method for p-value adjustment, passed to stats::p.adjust(). Default "BH".

alpha

Significance level for the significant column. Default 0.05.

Value

A tibble with columns: isodecoder, pos1, pos2, mean_log_or_num, mean_log_or_den, se_num, se_den, ror, ror_se, z_score, p_value, p_adj, ci_lower, ci_upper, and significant.

Examples

num <- tibble::tibble(
  isodecoder = rep("tRNA-Ala-AGC", 2),
  pos1 = c(20, 34), pos2 = c(34, 58),
  mean_or = c(3.0, 1.5), mean_log_or = c(1.1, 0.4),
  sd_log_or = c(0.2, 0.3), min_pval = c(0.001, 0.01),
  total_reads = c(500, 300), n_copies = c(2, 2)
)
den <- tibble::tibble(
  isodecoder = rep("tRNA-Ala-AGC", 2),
  pos1 = c(20, 34), pos2 = c(34, 58),
  mean_or = c(1.5, 1.2), mean_log_or = c(0.4, 0.18),
  sd_log_or = c(0.15, 0.25), min_pval = c(0.01, 0.05),
  total_reads = c(400, 250), n_copies = c(2, 2)
)
compute_ror_isodecoder(num, den)
#> # A tibble: 2 × 15
#>   isodecoder    pos1  pos2 mean_log_or_num se_num mean_log_or_den se_den   ror
#>   <chr>        <dbl> <dbl>           <dbl>  <dbl>           <dbl>  <dbl> <dbl>
#> 1 tRNA-Ala-AGC    20    34             1.1    0.2            0.4    0.15  0.7 
#> 2 tRNA-Ala-AGC    34    58             0.4    0.3            0.18   0.25  0.22
#> # ℹ 7 more variables: ror_se <dbl>, z_score <dbl>, p_value <dbl>, p_adj <dbl>,
#> #   ci_lower <dbl>, ci_upper <dbl>, significant <lgl>