Calculates the mean value and confidence interval, as well as standard deviation and standard error of the mean, for every column in an input table. Confidence intervals are calculated using the "Empirical bootstrap" technique (based on random sampling with replacement). The input will typically be a table of signal values for different obervations (across rows) over a set of positions (across columns).
signal_mean_and_ci(signal_data, ci = 0.95, rep_bootstrap = 1000, na_rm = TRUE)
signal_data | Input signal data matrix (or an object that can be coerced
to class |
---|---|
ci | Numeric value between 0 and 1 representing the confidence interval
percentage. Defaults to |
rep_bootstrap | Integer specifying the number of times to repeat the
bootstrapping procedure. Defaults to |
na_rm | Logical indicating whether to remove |
A matrix with as many rows as there are columns in the input and three columns:
Mean
Input column mean
Lower
Lower limit of the bootstrapping confidence interval
Upper
Upper limit of the bootstrapping confidence interval
SD
Standard deviation
SEM
Standard error of the mean
# NOT RUN { signal_mean_and_ci(WT_signal_at_orf) signal_mean_and_ci(WT_signal_at_summits, ci=0.90) signal_mean_and_ci(WT_signal_at_dsb, bootstrap_reps=5000) # }