b0_plotprxy: Predictive X-Y Plot In snoweye/cubfits: Codon Usage Bias Fits

Description

This utility function provides a basic plot of production rates.

Usage

 ```1 2 3 4 5 6 7 8``` ``` plotprxy(x, y, x.ci = NULL, y.ci = NULL, log10.x = TRUE, log10.y = TRUE, add.lm = TRUE, add.one.to.one = TRUE, weights = NULL, add.legend = TRUE, xlim = NULL, ylim = NULL, xlab = "Predicted Production Rate (log10)", ylab = "Observed Production Rate (log10)", main = NULL) ```

Arguments

 `x` expression values. `y` expression values, of the same length of `x`. `x.ci` confidence interval of `x`, of dimension `length{x} * 2`, for outliers labeling. `y.ci` confidence interval of `y`, of dimension `length{y} * 2`, for outliers labeling. `log10.x` `log10()` and mean transformation of x axis. `log10.y` `log10()` and mean transformation of y axis. `add.lm` if add `lm()` fit. `add.one.to.one` if add one-to-one line. `weights` weights to `lm()`. `add.legend` if add default legend. `xlim` limits of x-axis. `ylim` limits of y-axis. `xlab` an option passed to `plot()`. `ylab` an option passed to `plot()`. `main` an option passed to `plot()`.

Details

As the usual X-Y plot where `x` and `y` are expression values.

If `add.lm = TRUE` and `weights` are given, then both ordinary and weighted least squares results will be plotted.

Value

A scatter plot with a fitted `lm()` line and R squared value.

Author(s)

Wei-Chen Chen [email protected].

References

`plotbin()` and `plotmodel()`.
 ```1 2 3 4 5 6 7 8``` ```## Not run: suppressMessages(library(cubfits, quietly = TRUE)) y.scuo <- convert.y.to.scuo(ex.train\$y) SCUO <- calc_scuo_values(y.scuo)\$SCUO plotprxy(ex.train\$phi.Obs, SCUO) ## End(Not run) ```