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Report the representative datapoints in a SuperPlot

Source: R/representative.R
representative.Rd

This function finds the representative datapoints for each condition and replicate in a SuperPlot dataset. It calculates the mean or median of the replicates (conditions), then ranks the individual measurements by their difference from the summary statistic. The function returns a data frame with the representative datapoints for each treatment and replicate, along with their rank of difference from the summary statistic.

Usage

representative(
  df,
  meas,
  cond,
  repl,
  label = "",
  bars = "",
  rep_summary = "rep_mean",
  outlier = FALSE
)

Arguments

df

data frame with at least three columns: meas, cond, repl

meas

character name of column with measurement (e.g. intensity)

cond

character name of column with condition (e.g. Control, WT)

repl

character name of column with replicate (e.g. unique experiment identifiers)

label

character name of column with labels for measurements (e.g. file names), optional.

bars

string to specify the summary stats of replicate sumaries, select ("none" default, "mean_sd", "mean_sem", or "mean_ci"). Sepcifying this overrides the rep_summary argument

rep_summary

string for summary statistic to use for replicates, select ("rep_mean" default, or "rep_median")

outlier

logical, if TRUE then ranking is reversed to find the most extreme datapoint in each treatment and replicate, default is FALSE.

Value

data frame with the representative datapoints for each treatment and replicate, with the rank of the difference from the summary statistic.

Details

The top ranked datapoint for each treatment and replicate is printed to the console. This is useful for identifying the most representative datapoint for each condition, which can be used for showing in a figure.

A label column can be specified to identify the datapoint (this could be a file name or other identifier). If no label is specified, the row number is used instead.

Examples

representative(lord_jcb,
  "Speed", "Treatment", "Replicate")
#> # A tibble: 6 × 6
#>   Treatment Replicate Speed rowno     diff  rank
#>   <chr>     <chr>     <dbl> <int>    <dbl> <int>
#> 1 Control   1          41.5     5 0.0524       1
#> 2 Control   2          32.9    98 0.220        1
#> 3 Control   3          20.7   124 0.0541       1
#> 4 Drug      1          29.4   178 0.217        1
#> 5 Drug      2          22.3   207 0.000237     1
#> 6 Drug      3          12.9   285 0.0113       1
#> # A tibble: 300 × 6
#>    Treatment Replicate Speed rowno   diff  rank
#>    <chr>     <chr>     <dbl> <int>  <dbl> <int>
#>  1 Control   1          41.5     5 0.0524     1
#>  2 Control   1          41.4    13 0.0875     2
#>  3 Control   1          41.9     2 0.366      3
#>  4 Control   1          42.2    31 0.688      4
#>  5 Control   1          40.2    26 1.26       5
#>  6 Control   1          39.6    36 1.86       6
#>  7 Control   1          39.5    37 1.97       7
#>  8 Control   1          43.7     1 2.20       8
#>  9 Control   1          39.2    27 2.24       9
#> 10 Control   1          43.8    17 2.27      10
#> # ℹ 290 more rows