Package {BKMutate}

BKMutate: Statistical Analysis of Induced Mutagenesis Experiments

Description

A colour-first toolkit for analysing induced mutagenesis experiments in crop plants: dose-response and LD50/GR50 with Fieller intervals, mutagenic effectiveness and efficiency with confidence intervals, chlorophyll mutation spectrum analysis, generalised linear models for M2 counts, and formal comparison of mutagens.

Author(s)

Praveen Kumar B. K. bkpraveenars@gmail.com

See Also

bm_dose, bm_effect, bm_spectrum, bm_m2, bm_compare, bm_plot.

Formal comparison of mutagens

Description

Compares mutagens using interval estimates: pooled mutation frequency with Wilson intervals, pairwise ratios of mutation frequency with Katz intervals and chi-square tests, and relative biological effectiveness computed from LD50 values.

Usage

bm_compare(effect, dose_fit = NULL, reference = NULL, conf = 0.95)

Arguments

Value

An object of class bm_compare with pooled frequencies, pairwise ratios and relative biological effectiveness.

Examples

m <- bm_data("m2")
ef <- bm_effect(m, "mutagen", "dose", "M2_plants", "M2_mutants",
                lethality_n = "lethality_n", lethality_x = "lethality_x",
                boot = 0)
cmp <- bm_compare(ef)
cmp
bm_plot(cmp)

Load a bundled BKMutate example dataset

Description

Convenience loader for the demonstration datasets shipped with the package.

Usage

bm_data(name = c("dose", "m2", "spectrum", "counts"))

Arguments

Value

A data frame.

Examples

head(bm_data("dose"))

Dose-response analysis: LD50 and GR50 with Fieller confidence intervals

Description

Fits a dose-response model and estimates the median lethal dose (LD50) or median growth-reduction dose (GR50). Because the median effective dose is a ratio of two correlated coefficients, its confidence interval is obtained from Fieller's theorem, which is correctly asymmetric; the symmetric delta-method interval is reported alongside.

Usage

bm_dose(data, dose, n_total = NULL, n_affected = NULL, response = NULL,
        mutagen = NULL, link = c("probit", "logit", "cloglog"), conf = 0.95)

Arguments

Value

An object of class bm_dose containing the estimates, fitted curve and observed points.

References

Fieller EC (1954). Some problems in interval estimation. Journal of the Royal Statistical Society B 16, 175–185. doi:10.1111/j.2517-6161.1954.tb00159.x

See Also

bm_effect, bm_plot

Examples

d <- bm_data("dose")
res <- bm_dose(d, dose = "dose", n_total = "n_treated",
               n_affected = "n_survived", mutagen = "mutagen")
res
bm_plot(res)

Mutagenic effectiveness and efficiency with confidence intervals

Description

Estimates mutagenic effectiveness (mutation frequency per unit dose) and mutagenic efficiency (mutation frequency per unit biological damage) with interval estimates. Effectiveness intervals rescale a Wilson score interval. Efficiency is a ratio of two binomial proportions, formally a relative risk, so intervals are obtained by the delta method on the log scale (Katz) and by the nonparametric bootstrap. Conventional practice reports these quantities as point estimates only.

Usage

bm_effect(data, mutagen, dose, m2_total, m2_mutants,
          lethality_n = NULL, lethality_x = NULL,
          sterility_n = NULL, sterility_x = NULL, injury = NULL,
          conf = 0.95, boot = 2000, seed = 1L)

Arguments

Value

An object of class bm_effect containing point estimates and interval estimates for mutation frequency, effectiveness and efficiency.

References

Konzak CF, Nilan RA, Wagner J, Foster RJ (1965). Efficient chemical mutagenesis.
Katz D, Baptista J, Azen SP, Pike MC (1978). Obtaining confidence intervals for the risk ratio in cohort studies. Biometrics 34, 469–474. doi:10.2307/2530610

See Also

bm_compare

Examples

m <- bm_data("m2")
res <- bm_effect(m, mutagen = "mutagen", dose = "dose",
                 m2_total = "M2_plants", m2_mutants = "M2_mutants",
                 lethality_n = "lethality_n", lethality_x = "lethality_x",
                 boot = 200)
res
bm_plot(res)
bm_plot(res, type = "efficiency")

Generalised linear models for M2 mutant counts

Description

Fits a Poisson log-linear model to per-family mutant counts, tests for overdispersion, and refits as quasi-Poisson when the counts are overdispersed. The number of plants scored enters as an offset so the model describes the mutation rate per plant.

Usage

bm_m2(data, counts, mutagen, dose = NULL, plants = NULL,
      family = c("auto", "poisson", "quasipoisson"),
      scale_dose = TRUE, disp_threshold = 1.5)

Arguments

Value

An object of class bm_m2 with the coefficient table, dispersion statistic and fitted model.

Examples

cts <- bm_data("counts")
res <- bm_m2(cts, counts = "mutants", mutagen = "mutagen",
             dose = "dose", plants = "plants")
res
bm_plot(res)

BKMutate colour palettes

Description

Palettes designed for mutagenesis figures, including a chlorophyll palette echoing the mutant classes themselves.

Usage

bm_palette(name = c("mutagen", "chloro", "dose", "damage", "contrast"),
           n = NULL, reverse = FALSE)

Arguments

Value

A character vector of hex colours.

Examples

bm_palette("chloro")
bm_palette("dose", 8)

Draw the signature figure for a BKMutate result

Description

Generic entry point returning the publication-ready figure for whichever analysis produced x.

Usage

bm_plot(x, ...)

Arguments

Value

A ggplot2 object.

Examples

bm_plot(bm_dose(bm_data("dose"), "dose", "n_treated", "n_survived",
                mutagen = "mutagen"))

Chlorophyll mutation spectrum analysis

Description

Summarises the spectrum of chlorophyll-deficient mutants, tests whether the spectrum differs between mutagens by a chi-square test of homogeneity, and quantifies spectrum breadth by the Shannon-Weaver diversity index and its evenness.

Usage

bm_spectrum(data, mutagen, classes, dose = NULL)

Arguments

Value

An object of class bm_spectrum with counts, relative frequencies, diversity indices and a homogeneity test.

Examples

s <- bm_data("spectrum")
res <- bm_spectrum(s, mutagen = "mutagen",
                   classes = c("albina","xantha","chlorina","viridis"),
                   dose = "dose")
res
bm_plot(res)

Discrete BKMutate colour and fill scales

Description

Discrete colour and fill scales built on the BKMutate palettes.

Usage

scale_colour_bm(pal_name = "mutagen", reverse = FALSE, ...)

scale_color_bm(pal_name = "mutagen", reverse = FALSE, ...)

scale_fill_bm(pal_name = "mutagen", reverse = FALSE, ...)

Arguments

Value

A ggplot2 scale.

Examples

library(ggplot2)
ggplot(iris, aes(Sepal.Length, Sepal.Width, colour = Species)) +
  geom_point() + scale_colour_bm("contrast")

A clean ggplot2 theme for BKMutate figures

Description

The BKMutate figure theme.

Usage

theme_bm(base_size = 12, base_family = "", grid = TRUE)

Arguments

Value

A ggplot2 theme object.

Examples

library(ggplot2)
ggplot(mtcars, aes(wt, mpg)) + geom_point() + theme_bm()