Plots multiple b-scored normalised platemaps

Description

Transforms numerical values using the b-score normalisation process to account for row and column effects. Uses well and plate labels to plot the normalised values in the form of microtitre plates. Works for 96, 384 and 1536 well plates.

Usage

b_grid(
  data,
  well,
  plate_id,
  plate = 96,
  eps = 0.01,
  maxiter = 10,
  trace.iter = FALSE,
  na.rm = FALSE,
  ...
)

Arguments

Value

ggplot plot

Examples

df01 <- data.frame(well = num_to_well(1:96),
                   vals = rnorm(96),
                   plate = 1)

df02 <- data.frame(well = num_to_well(1:96),
                   vals = rnorm(96),
                   plate = 2)

df <- rbind(df01, df02)

b_grid(data = df$vals,
       well = df$well,
       plate_id = df$plate,
       plate = 96)

Plots a heatmap of b-score normalised values in a plate layout

Description

Transforms numerical values using the b-score normalisation process to account for row and column effects. Uses well labels to plot the normalised values in the form of a microtitre plate. Works for 6, 12, 24, 48, 96, 384 or 1536 well plates

Usage

b_map(
  data,
  well,
  normalise = FALSE,
  plate = 96,
  eps = 0.01,
  maxiter = 10,
  trace.iter = FALSE,
  na.rm = TRUE,
  ...
)

Arguments

Value

ggplot plot

Examples

df <- data.frame(well = num_to_well(1:96),
vals = rnorm(96))

b_map(data = df$vals,
     well = df$well,
     plate = 96)

df_384 <- data.frame(
         well = num_to_well(1:384, plate = 384),
         vals = rnorm(384))

b_map(data = df_384$vals,
     well = df_384$well,
     plate = 384)

2 way median polish

Description

2 way median polish to remove plate effects such as row/column/edge effects. Given a dataframe containing alpha-numeric wellIDs and numerical values, this b_score will return a dataframe of the same structure after a two-way median smooth.

Usage

b_score(data, well, plate, plate_id = NULL, normalise = FALSE)

Arguments

Examples

df <- data.frame(well = num_to_well(1:96),
                 vals = rnorm(96))

b_score(data = df$vals,
        well = df$well,
        plate = 96)

Platemap to identify 'hits' following a B-score normalisation

Description

Produces a platemap with colours indicating wells above or below selected threshold after normalising for systematic plate effects via B-score smooth. The threshold is definined calculated from a z-score, i.e plus or minus standard deviations from the plate mean.

Usage

bhit_map(
  data,
  well,
  plate = 96,
  threshold = 2,
  palette = "Spectral",
  eps = 0.01,
  maxiter = 10,
  trace.iter = FALSE,
  na.rm = TRUE,
  ...
)

Arguments

Value

ggplot plot

Examples

df <- data.frame(vals = rnorm(384),
   well = num_to_well(1:384, plate = 384))

bhit_map(data = df$vals,
   well = df$well,
   plate = 384,
   threshold = 3)

checks plate input for dodgy well plate combinations

Description

checks plate input for dodgy well plate combinations

Usage

check_plate_input(well, plate)

Arguments

Plots distributions per well in a plate layout

Description

Produces distribution plots facetted in a plate-layout format.

Usage

dist_map(well, data)

Arguments

Value

ggplot plot

Fill in missing wells

Description

Fills in missing wells with rows of NA values. Useful for any functions that require a complete plate such as 'b_score'.

Usage

fill_plate(df, well, plate = 96)

Arguments

Value

dataframe

Examples

vals <- rnorm(96) ; wells <- num_to_well(1:96)
df <- data.frame(wells, vals)
df_missing <- df[-c(1:10), ]
fill_plate(df_missing, "wells")

Plots multiple platemaps with and identifies hits

Description

Converts numerical values and well labels into 'hits' in the form of multiple plate maps. Hits are calculated as wells above or below a specified number of standard deviations from the overall average

Usage

hit_grid(
  data,
  well,
  plate_id,
  threshold = 2,
  ncols = 2,
  plate = 96,
  each = FALSE,
  scale_each = FALSE,
  palette = "Spectral",
  ...
)

Arguments

Value

ggplot plot

Examples

df01 <- data.frame(well = num_to_well(1:96),
  vals = rnorm(96),
  plate = 1)

df02 <- data.frame(well = num_to_well(1:96),
  vals = rnorm(96),
  plate = 2)

df <- rbind(df01, df02)

hit_grid(data = df$vals,
    well = df$well,
    plate_id = df$plate,
    plate = 96,
    each = FALSE)

Platemap to identify 'hits' in a screen

Description

Produces a plot in the form of a micro-titre layout, with colours indicating wells above or below a nominated threshold.

Usage

hit_map(data, well, plate = 96, threshold = 2, palette = "Spectral", ...)

Arguments

Value

ggplot plot

Examples

df <- data.frame(vals = rnorm(1:384),
                 well = num_to_well(1:384, plate = 384))

hit_map(data = df$vals,
        well = df$well,
        plate = 384,
        threshold = 3)

internal 1536 plate function for plate_map

Description

internal 1536 plate function for plate_map

Usage

is_1536(well)

Arguments

check ggplot2 version

Description

after ggplot2 v3.3.0, using scale_y_reverse() also reverses the order of the ylim arguments in coord_fixed()

Usage

is_old_ggplot()

change legend title

Description

Change the legend title. This can be done in ggplot but there are a million incomprehensible ways to do it.

Usage

legend_title(title)

Arguments

Value

ggplot object

Converts list to a dataframe in a sensible way

Description

Given a list of dataframes with the same columns, this function will row bind them together, and if passed a col_name arguement, will produce a column containing their original element name

Usage

list_to_dataframe(l, col_name = NULL)

Arguments

Value

dataframe

2-way median smooth

Description

Given a platemap produced by plate_map, will return a dataframe with after values have been transformed into a matrix mirroring the plate structure and undergoing a 2-way median polish to remove row or column effects

Usage

med_smooth(
  platemap,
  plate,
  eps = 0.01,
  maxiter = 10,
  trace.iter = FALSE,
  na.rm = TRUE,
  normalise = FALSE
)

Arguments

Value

A dataframe consisting of two column, wellID and polished numeric values

Returns wells that are missing from a complete plate

Description

Returns a vector of wells that are missing from a complete plate.

Usage

missing_wells(df, well, plate = 96)

Arguments

Value

vector of missing wells

Examples

vals <- rnorm(96) ; wells <- num_to_well(1:96)
df <- data.frame(vals, wells)
df_missing <- df[-c(1:10), ]
missing_wells(df_missing, "wells")

Converts numbers to well labels

Description

Converts numerical values to corresponding alpha-numeric well labels for 6, 12, 24, 48, 96, 384 or 1536 well plates. Note, it's advisable to specify the number of wells in 'plate'.

Usage

num_to_well(x, plate = 96)

Arguments

Value

Vector of alpha-numeric well labels

Examples

num_to_well(1:96)
num_to_well(1:96, plate = 384)

nums <- c(1:10, 20:40, 60:96)
num_to_well(nums)

Plots multiple platemaps as a heatmap of the first principal component.

Description

Converts multivariate data and well labels into a heatmap of the first principal component in the form of a grid of platemaps.

Usage

pc_grid(data, well, plate_id, ncols = 2, plate = 96, ...)

Arguments

Value

ggplot plot

Examples

df01 <- data.frame(
  well = num_to_well(1:96),
  plate = 1,
  vals1 = rnorm(1:96),
  vals2 = rnorm(1:96))

df02 <- data.frame(
  well = num_to_well(1:96),
  plate = 2,
  vals1 = rnorm(1:96),
  vals2 = rnorm(1:96))

df <- rbind(df01, df02)

pc_grid(data = df[, 3:4],
        well = df$well,
        plate_id = df$plate,
        plate = 96)

Principal component heatmap in a plate layout

Description

Takes the values and well identifiers, calculates the first principal component, scales and plots the component as a heatmap in the form of a 96 or 384-well plate. A way to quickly show variation of multi-parametric data within a plate.

Usage

pc_map(data, well, plate = 96, ...)

Arguments

Value

gplot plot

Examples

df <- data.frame(
  well = num_to_well(1:96),
  vals1 = rnorm(1:96),
  vals2 = rnorm(1:96))

pc_map(data = df[, 2:3],
       well = df$well,
       plate = 96)

Plots multiple heatmaps identifying hits from the first principal component

Description

Converts numerical values, well labels, and plate labels into multiple heatmaps of plates, with z-scored principal components coloured dependent on a specified threshold of standard deviations above or below the average.

Usage

pchit_grid(data, well, plate_id, ...)

Arguments

Value

ggplot plot

Examples

df01 <- data.frame(
  well = num_to_well(1:96),
  plate = 1,
  vals1 = rnorm(1:96),
  vals2 = rnorm(1:96))

df02 <- data.frame(
  well = num_to_well(1:96),
  plate = 2,
  vals1 = rnorm(1:96),
  vals2 = rnorm(1:96))

df <- rbind(df01, df02)

pchit_grid(data = df[,3:4],
           well = df$well,
           plate_id = df$plate,
           plate = 96)

Plots a heatmap identifying hits from the first principal component

Description

Converts numerical values and plate labels intoa plate heatmap with z-scored principal components coloured dependent on a specified threshold of standard deviations above or below the average.

Usage

pchit_map(data, well, plate = 96, threshold = 2, palette = "Spectral", ...)

Arguments

Value

ggplot plot

Examples

v1 <- rnorm(1:96)
v2 <- rnorm(1:96)
v3 <- rnorm(1:96)
wells <- num_to_well(1:96)
df <- data.frame(wells, v1, v2, v3)


pchit_map(data = df[, 2:4],
          well = df$wells,
          threshold = 1.5)

Two way-median smooth on a plate map

Description

Given a platemap produced by plate_map, this will perform a two way median smooth, and return the results of medpolish. Useful for row and column effects, as well as the raw residuals.

Usage

plate_effect(platemap, plate)

Arguments

creates dataframe of row,column,data from wellID and data

Description

internal function

Usage

plate_map(data, well)

Arguments

Value

dataframe

creates dataframe of row, column, plate_id from data regarding wellIDs

Description

internal function

Usage

plate_map_grid(data, well, plate_id)

Arguments

Value

dataframe

creates dataframe of row, column, plate_id from data regarding wellIDs

Description

internal function

Usage

plate_map_grid_scale(data, well, plate_id, each)

Arguments

Value

dataframe

row, column for multiple features

Description

Generates a dataframe for multiple features, given a wellID column and multiple features

Usage

plate_map_multiple(data, well)

Arguments

creates dataframe of row, column, and scaled data from well IDs

Description

internal function

Usage

plate_map_scale(data, well)

Arguments

Value

dataframe

plate layout matrix from well IDs

Description

Given a dataframe of alpha-numeric well IDs e.g ("A01"), and values, this function will produce a matrix in the form of a plate layout.

Usage

plate_matrix(data, well, plate = 96)

Arguments

Value

matrix

Examples

a <- 1:96
wells <- num_to_well(1:96)
plate_matrix(data = a, well = wells)

x <- rnorm(384)
wells <- num_to_well(1:384, plate = 384)
plate_matrix(data = x, well = wells, plate = 384)

ggplot plate object

Description

internal function

Usage

plt12(
  platemap,
  size = 38,
  shape = 21,
  na_fill = "white",
  na_alpha = 0.1,
  na_size_ratio = 0.9
)

Arguments

Value

ggplot object

ggplot plate object

Description

internal function

Usage

plt1536(
  platemap,
  size = 3.5,
  shape = 22,
  na_fill = "white",
  na_size_ratio = 0.95,
  na_alpha = 0.1
)

Arguments

Value

ggplot object

ggplot plate object

Description

internal function

Usage

plt24(
  platemap,
  size = 26,
  shape = 21,
  na_fill = "white",
  na_size_ratio = 0.9,
  na_alpha = 0.1
)

Arguments

Value

ggplot object

ggplot plate object

Description

internal function

Usage

plt384(
  platemap,
  size = 5,
  shape = 22,
  na_fill = "white",
  na_size_ratio = 0.95,
  na_alpha = 0.1
)

Arguments

Value

ggplot object

ggplot plate object

Description

internal function

Usage

plt48(
  platemap,
  size = 18,
  shape = 21,
  na_fill = "white",
  na_size_ratio = 0.9,
  na_alpha = 0.1
)

Arguments

Value

ggplot object

ggplot plate object

Description

internal function

Usage

plt6(
  platemap,
  size = 50,
  shape = 21,
  na_fill = "white",
  na_alpha = 0.1,
  na_size_ratio = 0.9
)

Arguments

Value

ggplot object

ggplot plate object

Description

internal function

Usage

plt96(
  platemap,
  size = 10,
  shape = 21,
  na_fill = "white",
  na_size_ratio = 0.9,
  na_alpha = 0.1
)

Arguments

Value

ggplot object

Plots multiple platemaps with heatmap of raw values

Description

Converts numerical values. well labels, and plate labels into multiple plate heatmaps

Usage

raw_grid(data, well, plate_id, ncols = 2, plate = 96, ...)

Arguments

Value

ggplot plot

Examples

df01 <- data.frame(well = num_to_well(1:96),
  vals = rnorm(96),
  plate = 1)

df02 <- data.frame(well = num_to_well(1:96),
  vals = rnorm(96),
  plate = 2)

df <- rbind(df01, df02)

raw_grid(data = df$vals,
    well = df$well,
    plate_id = df$plate,
    plate = 96)

Plots a platemap with heatmap of raw values

Description

Converts numerical values and well labels into multiple plate heatmaps

Usage

raw_map(data, well, plate = 96, ...)

Arguments

Value

ggplot plot

Examples

df <- data.frame(vals = rnorm(1:384),
  well = num_to_well(1:384, plate = 384))

raw_map(data = df$vals,
        well = df$well,
        plate = 384)

Annotates dataframe with metadata in a platemap matrix

Description

Annotates a dataframe containined well identifiers with metadata in the form of a platemap matrix, matching the existing well-labels to the well position in the platemap

Usage

read_map(data, map, verbose = TRUE, new_col_name = "header")

Arguments

Value

dataframe with new column named after 'new_col_name'

example data in a plate map form

Description

example data in a plate map form

Usage

readmap_data

Format

96 integers structured in a the form of a 96-well plate

Source

none

rotates matrix by 180 degrees

Description

If someone (no names) puts in a plate upside down, this function will rotate a plate matrix produced by plate_matrix to be the correct way up. I.e if A01 is in the bottom right hand corner rather than the top left.

Usage

rotate_plate(m)

Arguments

Value

matrix

Set values in rectangular areas of a plate

Description

Updates a table representing a multiwell plate, by setting a given value for all wells in a block or a list of blocks defined by the well coordinates of their upper-left and bottom-right corners.

Usage

set_block(plate, block, what, value)

Arguments

Value

Returns the ‘plate’ table, where the values for the wells indicated in the blocks have been updated.

Author(s)

Charles Plessy

See Also

num_to_well

Examples

p <- data.frame(well = num_to_well(1:96))
head(p)

p <- set_block(p, c("A01~B02", "A05~D05"), "dNTP", 0.25)
p <- set_block(p,   "A03",                 "dNTP", 0.50)
head(p)

# Be careful with the column names
p <- set_block(p, "A01~H12", "Mg2+", 3.0)
head(p)

## Not run: 
# Chained updates with magrittr
p %<>%
  setBlock("A01~C04", "dNTP", 0.5) %>%
  setBlock("A01~C04", "Mg",   3.0)

## End(Not run)

Converts well labels to numbers

Description

Converts alpha-numeric well labels to numbers corresponding to positions within a microtitre plate. Either 96 or 384 well plate, in column-wise order or in a column snaking pattern.

Usage

well_to_num(wells, style = "normal", plate = 96)

Arguments

Value

Vector of numbers

Examples

well_to_num("A01")

well_to_num("P12", plate = 384)

well_to_num("P12", plate = 384, style = "snake")

wells <- c("A01", "A02", "A03")
well_to_num(wells)

Plots multiple platemaps with heatmap of scaled values

Description

Converts numerical values. well labels, and plate labels into multiple plate heatmaps

Usage

z_grid(
  data,
  well,
  plate_id,
  ncols = 2,
  plate = 96,
  each = FALSE,
  scale_each = FALSE,
  ...
)

Arguments

Value

ggplot plot

Examples

df01 <- data.frame(well = num_to_well(1:96),
  vals = rnorm(96),
  plate = 1)

df02 <- data.frame(well = num_to_well(1:96),
  vals = rnorm(96),
  plate = 2)

df <- rbind(df01, df02)

z_grid(data = df$vals,
       well = df$well,
       plate_id = df$plate,
       plate = 96)

Plots a platemap with heatmap of scaled values

Description

Converts numerical values and well labels into multiple plate heatmaps

Usage

z_map(data, well, plate = 96, ...)

Arguments

Value

ggplot plot

Examples

df <- data.frame(vals = rnorm(1:384),
  well = num_to_well(1:384, plate = 384))

z_map(data = df$vals,
      well = df$well,
      plate = 384)