Type: Package
Title: Process Biological Impedance Sensing Data
Version: 0.1.4
Description: Process complex impedance sensing datasets, including those generated by ECIS, xCELLigence and cellZscope instruments. Data can be imported to a standardised tidy format and then plotted. Support for conducting and plotting the outputs of ANOVA (with appropriate tests of statistical assumptions) and cross-correlation analysis. For data processed using this package see Hucklesby et al. (2020) <doi:10.3390/bios11050159>.
License: GPL (≥ 3)
URL: https://github.com/JamesHucklesby/vascr
BugReports: https://github.com/JamesHucklesby/vascr/issues
Depends: R (≥ 3.6)
Imports: cli, dplyr, doFuture, foreach, furrr, ggnewscale, ggplot2, ggpubr, progressr, ggtext, glue, memoise, multcomp, patchwork, rlang, rstatix, stringr, tidyr, utils, ggrepel, nlme
Suggests: bslib, DBI, DT, data.table, future, odbc, purrr, readr, readxl, shiny, shinyjs, testthat (≥ 3.0.0), vdiffr, writexl, testthat, diffviewer
Config/testthat/edition: 3
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 7.3.3
NeedsCompilation: no
Packaged: 2026-02-04 00:31:12 UTC; James
Author: James JW Hucklesby ORCID iD [cre, aut, cph], Charles Unsworth ORCID iD [aut], E Scott Graham ORCID iD [aut], Catherine E angel ORCID iD [aut]
Maintainer: James JW Hucklesby <james.hucklesby@auckland.ac.nz>
Repository: CRAN
Date/Publication: 2026-02-06 19:50:02 UTC

vascr: Process Biological Impedance Sensing Data

Description

Process complex impedance sensing datasets, including those generated by ECIS, xCELLigence and cellZscope instruments. Data can be imported to a standardised tidy format and then plotted. Support for conducting and plotting the outputs of ANOVA (with appropriate tests of statistical assumptions) and cross-correlation analysis. For data processed using this package see Hucklesby et al. (2020) doi:10.3390/bios11050159.

Author(s)

Maintainer: James JW Hucklesby james.hucklesby@auckland.ac.nz (ORCID) [copyright holder]

Authors:

See Also

Useful links:

re-export magrittr pipe operator

Description

re-export magrittr pipe operator

re-export tribble

re-export glue

Value

Various outputs, please see documentation for source package

description Used to easily make pipe operator available

A tibble, made available for easy data entry manually

A string with glue substitution completed

Import all ECIS values, a child of ecis_import_raw and ecis_import_model

Description

Import all ECIS values, a child of ecis_import_raw and ecis_import_model

Usage

ecis_import(raw = NULL, modeled = NULL, experimentname = NULL)

Arguments

raw

A raw ABP file to import

modeled

A modeled APB file for import

experimentname

Name of the experiment to be built into the dataset

Value

A data frame containing all the data APB generated from an experiment

Examples


raw = system.file('extdata/instruments/ecis_TimeResample.abp', package = 'vascr')
modeled = system.file('extdata/instruments/ecis_TimeResample_RbA.csv', package = 'vascr')
experimentname = "TEST"

#Then run the import

data = ecis_import(raw ,modeled,experimentname)
#head(data)

Vascr growth data

Description

A dataset containing the growth curves of hCMEC/D3 cell lines seeded at various densities. The variables are as follows:

Usage

growth.df

Format

A tibble with 346370 rows and 9 variables:

Time

The time at which the measurement was taken (hours)

Unit

The unit the measurement was taken in

Well

The well in which the measurement was taken

Value

The value of the measurement taken

Frequency

The frequency at which data was collected

Experiment

Name of the experiment

Instrument

The instrument data was collected on

SampleID

The numerical ID of the sample

Sample

The name of the treatment applied to the dataset

Source

Hucklesby 2020

Vascr growth data which is not resampled

Description

A dataset containing the growth curves of hCMEC/D3 cell lines seeded at various densities. This is a subset of 'growth.df', without the final stages of processing.

Usage

growth_unresampled.df

Format

A tibble with 346370 rows and 9 variables:

Time

The time at which the measurement was taken (hours)

Unit

The unit the measurement was taken in

Well

The well in which the measurement was taken

Value

The value of the measurement taken

Frequency

The frequency at which data was collected

Experiment

Name of the experiment

Instrument

The instrument data was collected on

SampleID

The numerical ID of the sample

Sample

The name of the treatment applied to the dataset

Source

Hucklesby 2020

Vascr growth data which is not re sampled

Description

A dataset containing the growth curves of hCMEC/D3 cell lines seeded at various densities. This is a subset of 'growth.df', with only Rb data for faster processing.

Usage

rbgrowth.df

Format

A tibble with 346370 rows and 9 variables:

Time

The time at which the measurement was taken (hours)

Unit

The unit the measurement was taken in

Well

The well in which the measurement was taken

Value

The value of the measurement taken

Frequency

The frequency at which data was collected

Experiment

Name of the experiment

Instrument

The instrument data was collected on

SampleID

The numerical ID of the sample

Sample

The name of the treatment applied to the dataset

Source

Hucklesby 2020

Small growth data set for testing

Description

Small growth data set for testing

Usage

small_growth.df

Format

A tibble with 346370 rows and 9 variables:

Time

The time at which the measurement was taken (hours)

Unit

The unit the measurement was taken in

Well

The well in which the measurement was taken

Value

The value of the measurement taken

Frequency

The frequency at which data was collected

Experiment

Name of the experiment

Instrument

The instrument data was collected on

SampleID

The numerical ID of the sample

Sample

The name of the treatment applied to the dataset

Source

Hucklesby 2020

Add a vertical line to a vascr line plot

Description

Add a vertical line to a vascr line plot

Usage

vascr_add_vline(plot, times.df)

Arguments

plot

The vascr plot to receive a vertical line (or lines)

times.df

A tibble containing "time", "color" and "label" columns to specify the addition of lines

Value

A labeled vascr plot

Examples

plot1_data = growth.df %>% vascr_subset(unit = "R", frequency = "4000")
plot1 = plot1_data %>% vascr_summarise("summary") %>% vascr_plot_line()

times.df = tribble(~time, ~label, ~colour, 100, "Test Point", "orange")
vascr_add_vline(plot1, times.df)

times.df = tribble(~time, ~label, 100, "ZTest Point", 150, "Test Point 2")
vascr_add_vline(plot1, times.df)

Apply a map to a vascr dataset

Description

Apply a map to a vascr dataset

Usage

vascr_apply_map(data.df, map)

Arguments

data.df

the dataset to apply to

map

the dataset to apply

Value

a named vascr dataset

Examples

lookup = system.file('extdata/instruments/eciskey.csv', package = 'vascr')
vascr_apply_map(data.df = growth.df, map = lookup)

vascr_apply_map(growth.df %>% vascr_subset(well = c("A1")), lookup)

Combine ECIS data frames end to end

Description

This function will combine ECIS data sets end to end. Preferential to use over a simple rbind command as it runs additional checks to ensure that data points are correctly generated

Usage

vascr_combine(..., resample = FALSE)

Arguments

...

List of data frames to be combined

resample

Automatically try and re sample the data set. Default is FALSE

Value

A single data frame containing all the data imported, automatically incremented by experiment

Examples

#Make three fake experiments worth of data
experiment1.df = vascr_subset(growth.df, experiment = "1")
experiment2.df = vascr_subset(growth.df, experiment = "2")
experiment3.df = vascr_subset(growth.df, experiment = "3")

data = vascr_combine(experiment1.df, experiment2.df, experiment3.df)
head(data)

Run ANOVA and Dunnett's comparisons on a vascr dataset

Description

Run ANOVA and Dunnett's comparisons on a vascr dataset

Usage

vascr_dunnett(data.df, unit, frequency, time, reference)

Arguments

data.df

A vascr dataset

unit

The unit to plot

frequency

The frequency to plot

time

The time to plot

reference

Reference sample to compare against. If all comparisons are needed use vascr_anova

Value

A table with the results of the Dunnett's test

Examples

vascr_dunnett(data.df = growth.df, unit = "R", frequency = 4000, time = 100, reference = 6)
vascr_dunnett(growth.df, "R", 4000, time = list(50, 100), 6)

Edit a sample name in a vascr dataframe

Description

Edit a sample name in a vascr dataframe

Usage

vascr_edit_name(data.df, to_remove, to_add = "")

Arguments

data.df

The data set to edit

to_remove

The sample to remove

to_add

The sample to replace with

Value

An edited vascr dataset

Examples

vascr_edit_name(growth.df,"HCMEC D3", "HCMEC/D3")

Rename a sample in a vascr dataset

Description

Renames samples in a vascr dataset, either replacing the whole sample or parts of the string.

Usage

vascr_edit_sample(data.df, change_list, partial = TRUE, escape = TRUE)

Arguments

data.df

Vascr dataset to update

change_list

List of vectors containing pairs of search and replacement terms to replace

partial

TRUE or FALSE, defines if partial matches should be changed

escape

TRUE or FALSE, whether to escape special characters passed into the function

Value

An updated vascr data frame

Examples

to_rename = growth.df %>% vascr_subset(sample = c("0 cells","20,000 cells", "10,000 cells"))

to_rename$Sample %>% unique()

renamed = vascr_edit_sample(to_rename, change_list = list(c("0_cells", "Cell Free")))
print(renamed$Sample %>% unique())

Exclude samples from a vascr dataset

Description

Exclude samples from a vascr dataset

Usage

vascr_exclude(data.df, well = NULL, experiment = NULL, sampleid = NULL)

Arguments

data.df

the vascr data set to exclude things from

well

wells to exclude

experiment

experiments to exclude

sampleid

sampleID (or vector or sampleIDs) to exclude from analysis

Value

A smaller vascr dataset

Examples

vascr_exclude(growth.df, c("A01", "E01"))
vascr_exclude(growth.df, sampleid = 1)

Separate names in a vascr data frame

Description

Separate names in a vascr data frame

Usage

vascr_explode(data.df)

Arguments

data.df

the dataset to separate

Value

a separated vascr dataset, with additional columns for each variable

Examples

vascr_explode(growth.df)

Export a vascr dataframe

Description

Export a vascr dataframe

Usage

vascr_export_prism(
  data.df,
  filepath = tempfile("test_export", fileext = ".xlsx"),
  level = "experiments"
)

Arguments

data.df

a vascr dataset to export

filepath

Path to save the dataframe in

level

Level of replication to export, defaults to experiments

Value

A dataframe in prism format, or writes to file if filepath specified

Examples

filepath = tempfile("test_export", fileext = ".xlsx")
to_export = growth.df %>% vascr_subset(unit = c("R", "Rb"), frequency = c(0,4000))
vascr_export_prism(to_export, filepath)

vascr_export_prism(to_export, filepath, level = "wells")

Find vascr variables

Description

These functions are utility functions that will detect if arguments are invalid, and attempt to repair them. Each type of variable has rules related to what values are possible in a valid vascr dataset.

Usage

vascr_find(data.df = vascr::growth.df, paramater, value = NA)

Arguments

data.df

The vascr dataset to reference, will default to the growth.df dataset if not specified

paramater

The parameter to search. Options are "Time", "Unit", "Well", "Frequency", "Sample", "Experiment", "SampleID" or "resampled"

value

the value to look up

Value

The valid vascr dataset.

Examples


vascr_find(growth.df, "Time")
vascr_find(growth.df, "Time", 66.97)
vascr_find(growth.df, "Time", NULL)

vascr_find(growth.df, "Unit")
vascr_find(growth.df, "Unit", "Rb")
vascr_find(growth.df, "Unit", NULL)

vascr_find(growth.df, "Well")
vascr_find(growth.df, "Well", "A1")

vascr_find(growth.df, "Sample")
vascr_find(growth.df, "Sample", "5000 cells")

vascr_find(growth.df, "Frequency")
vascr_find(growth.df, "Frequency", 4000)

vascr_find(growth.df, "Experiment")
vascr_find(growth.df, "Experiment", 1)

vascr_find(growth.df, "SampleID")
vascr_find(growth.df, "SampleID", 5)

vascr_find(growth.df, "resampled")

vascr_find(growth.df, "all")

Check the level of a vascr data frame

Description

Check the level of a vascr data frame

Usage

vascr_find_level(data)

Arguments

data

The data frame to analyse

Value

The level of the dataset analysed

Examples

vascr_find_level(growth.df)
vascr_find_level(vascr_summarise(growth.df %>% vascr_subset(unit= "Rb"), level = "experiments"))
vascr_find_level(vascr_summarise(growth.df %>% vascr_subset(unit= "Rb"), level = "summary"))

Print out the characteristics of the vascr data frame

Description

Print out the characteristics of the vascr data frame

Usage

vascr_find_metadata(data.df)

Arguments

data.df

the vascr data frame to interrogate

Value

prints out the parameters of the dataframe in question

Examples

vascr_find_metadata(growth.df)

Implode individual samples from a vascr dataset

Description

Implode individual samples from a vascr dataset

Usage

vascr_implode(data.df, cols = NULL)

Arguments

data.df

A vascr dataset to be imploded

cols

The columns to implode

Value

A vascr dataset with individual wells imploded

Examples

vascr_implode(growth.df)

Import an impedance datafile to vascr

Description

Import an impedance datafile to vascr

Usage

vascr_import(
  instrument = NULL,
  raw = NULL,
  modeled = NULL,
  experiment = NULL,
  shear = FALSE
)

Arguments

instrument

Instrument to import from, either ECIS, xCELLigence or cellZscope

raw

Path to raw data file

modeled

Path to modeled data file from manufacturer's software

experiment

Name for the experiment being imported

shear

True or False, is a shear plate used, as these have a different electrode layout. Defaults to False.

Value

A vascr dataset for subsequent analysis

Examples



# ECIS
raw = system.file('extdata/instruments/ecis_TimeResample.abp', package = 'vascr')
modeled = system.file('extdata/instruments/ecis_TimeResample_RbA.csv', package = 'vascr')
vascr_import("ECIS", raw, modeled, "ECIS_Data")

# xCELLigence
raw = system.file('extdata/instruments/xcell.plt', package = 'vascr')
# No modeling for this system
vascr_import("xCELLigence", raw, experiment = "xCELLigence")

# cellZscope
model = system.file("extdata/instruments/zscopemodel.txt", package = "vascr")
raw = system.file("extdata/instruments/zscoperaw.txt", package = "vascr")
vascr_import("cellzscope", raw, model, "cellZscope")

#' # ScioSpec
raw = system.file("extdata/instruments/ScioSpec", package = "vascr")
vascr_import("sciospec", raw, model, "ScioSpec")

Load a vascr dataset

Description

Load a vascr dataset

Usage

vascr_load(path)

Arguments

path

the path to a .vascr file containing the saved dataset

Value

A vascr dataset

Examples


path = system.file("extdata/test.vascr", package = "vascr")
vascr_load(path)

Normalize ECIS data to a single time point

Description

This function normalises each unique experiment/well combination to it's value at the specified time. Contains options to do this either by division or subtraction. Can be run twice on the same dataset if both operations are desired.

Usage

vascr_normalise(data.df, normtime, divide = FALSE)

Arguments

data.df

Standard vascr data frame

normtime

Time to normalize the data to

divide

If set to true, data will be normalized via a division. If set to false (default) data will be normalized by subtraction. Default is subtraction

Value

A standard ECIS dataset with each value normalized to the selected point.

Examples


data = vascr_normalise(growth.df, normtime = 100)
head(data)

Make a display with all the ANOVA analysis pre-conducted

Description

Make a display with all the ANOVA analysis pre-conducted

Usage

vascr_plot_anova(
  data.df,
  unit,
  frequency,
  time,
  reference = NULL,
  separate = "x",
  rotate = 45
)

Arguments

data.df

vascr dataset to plot

unit

unit to plot

frequency

frequency to plot

time

timepoint to plot at

reference

Sample to reference post-hoc analysis to

separate

Value to use when separating comparasons in the output (default x)

rotate

degrees of rotation used for labeling the X axis

Value

A matrix of different ANOVA tests

Examples


# Run, comparing only to a reference
vascr_plot_anova(data.df = small_growth.df, unit = "R", frequency = 4000, time = 100, 
          reference = "5,000_cells + HCMEC D3_line")

Plot out each replicate well in a grid, with QC overlays

Description

Plot out each replicate well in a grid, with QC overlays

Usage

vascr_plot_grid(data.df, threshold = 0.2)

Arguments

data.df

a vascr formatted data frame of single values

threshold

threshold at which a data point is determined to be an outlier

Value

A plot to be used for QC

Examples

grid.df = growth.df %>% vascr_subset(unit = "R", frequency = "4000", experiment  = 1)
vascr_plot_grid(grid.df)

Plot a line graph with vascr

Description

Plot a line graph with vascr

Usage

vascr_plot_line(
  data.df,
  errorbars = Inf,
  alpha = 0.3,
  text_labels = TRUE,
  facet_expt = TRUE,
  show_linetypes = TRUE,
  explanatory = FALSE
)

Arguments

data.df

The vascr data set to plot

errorbars

Type of error bars, Inf for ribbons, 0 for no errors and any integer to plot every nth line

alpha

Transparency of the error ribbon plotted

text_labels

Show or hide well labels

facet_expt

Facet out different experiments, defaults to TRUE

show_linetypes

Include the line type for each experiment in the key. Default TRUE

explanatory

Whether to include commentary about unit meaning on y axis (default TRUE)

Value

a ggplot containing the data

Examples

vascr_plot_line(data.df = growth.df %>% vascr_subset(unit = "Rb"))
vascr_plot_line(growth.df %>% vascr_subset(unit = "Rb") %>% vascr_summarise(level = "experiments"))
data.df = growth.df %>% vascr_subset(unit = "Rb") %>% vascr_summarise(level = "summary")
vascr_plot_line(data.df, text_labels = FALSE)

growth.df %>% vascr_subset(unit = "R", frequency = 4000)  %>%
vascr_plot_line(facet = FALSE)

growth.df %>% vascr_subset(unit = "R", frequency = 4000)  %>%
vascr_plot_line(explanatory = TRUE)

Create a line plot with Dunnett's statistics

Description

Create a line plot with Dunnett's statistics

Usage

vascr_plot_line_dunnett(
  data.df,
  unit = "R",
  frequency = 4000,
  time = 100,
  reference = "0_cells + HCMEC D3_Line",
  normtime = NULL
)

Arguments

data.df

A vascr dataset

unit

Unit to calculate

frequency

Frequency to calculate from

time

Time to calculate

reference

Sample to reference testing against

normtime

Time to normalise the line plot to, note this does not affect underlying statistical test

Value

A line plot, annotated with the P-values determined by Dunnett's test

Examples

vascr_plot_line_dunnett(small_growth.df, unit = "R", frequency = 4000, time = 25, 
    reference = "0_cells + HCMEC D3_Line")
vascr_plot_line_dunnett(small_growth.df, unit = "R", frequency = 4000, time = list(25,100), 
    reference = "0_cells + HCMEC D3_Line")
vascr_plot_line_dunnett(small_growth.df, unit = "R", frequency = 4000, time = 180, 
    reference = "20,000_cells + HCMEC D3_Line")

Plot the data re sampling process

Description

Plot the data re sampling process

Usage

vascr_plot_resample(
  data.df,
  unit = "R",
  frequency = "4000",
  well = "A01",
  newn = 20,
  plot = TRUE,
  rug = TRUE,
  points = FALSE
)

Arguments

data.df

Dataset to analyse

unit

Unit to use, defaults to R

frequency

Frequency to use, defaults to 4000

well

Well to use, defaults to A01 (or first well in plate)

newn

New number of timepoints to compare to current

plot

Return a ggplot or the underlying data. Defaults to TRUE, returning the plot.

rug

Show rug lot, defaults true

points

Show points, defaults to false

Value

A plot showing how well the resampled data conforms to the actual data set

Examples

vascr_plot_resample(growth.df)
vascr_plot_resample(growth.df, plot = FALSE)

Resample a vascr dataset

Description

Impedance sensing data is often not collected simultaneously, which creates issues summarising and plotting the data. This function interpolates these data to allow these downstream functions to happen.

Usage

vascr_resample_time(
  data.df,
  npoints = vascr_find_count_timepoints(data.df),
  t_start = min(data.df$Time),
  t_end = max(data.df$Time),
  rate = NULL,
  force_timepoint = NULL,
  include_disc = TRUE
)

Arguments

data.df

The vascr dataset to resample

npoints

Manually specificity the number of points to resample at, default is the same frequency as the input dataset

t_start

Time to start at

t_end

Time to end at

rate

Time between timepoints

force_timepoint

Force a specific timepoint to be part of the resample

include_disc

Add an additional data point either side of a discrepancy. Defaults TRUE

Value

An interpolated vascr dataset

Examples

# Automatically re sample, mimicking the input data as closely as possible
vascr_resample_time(growth.df)

# Fully controlled resample with advanced options
vascr_resample_time(growth.df, t_start = 5, t_end = 20, rate = 5, force = c(1,2,3))

List out the samples currently in a vascr data set

Description

List out the samples currently in a vascr data set

Usage

vascr_samples(data.df)

Arguments

data.df

The vascr data set to analyse

Value

A printout of the samples, Sample ID's and experiments where they occur

Examples

vascr_samples(growth.df)

Save a vascr dataset

Description

Save a vascr dataset

Usage

vascr_save(data.df, path)

Arguments

data.df

The vascr dataset to save

path

The path to save the file to

Value

A .vascr file containing a vascr dataset

Examples

path = tempfile()
vascr_save(growth.df, path = path)

Launch the vascr UI

Description

Launch the vascr UI

Usage

vascr_shiny(data.df)

Arguments

data.df

Data to preload into shiny app

Value

A shinyApp to work with vascr data

Examples

 if(interactive()){
   vascr_shiny()
 }

Subset a vascr data set based on a number of factors

Description

Subset a vascr data set based on a number of factors

Usage

vascr_subset(
  data.df,
  time = NULL,
  unit = NULL,
  well = NULL,
  frequency = NULL,
  experiment = NULL,
  instrument = NULL,
  sampleid = NULL,
  sample = NULL,
  subsample = NULL,
  remove_na_value = TRUE,
  remove_excluded = TRUE
)

Arguments

data.df

vascr data set to subset

time

Specified times. Individual values in a list will be subset out. If vectors are present in the list, values between the two most extreme values will be returned.

unit

Units to subset. These are checked for integrity against possible units and the dataset itself

well

Wells to select

frequency

Frequencies to include in the data set.

experiment

Experiments to include in the data set. Can be addressed either by name, or by the numerical order that they were loaded into vascr_combine in

instrument

Which instruments to include values from

sampleid

List of ID's to be used. Sample names will be re-ordered accordingly for display.

sample

Sample to subset

subsample

Frequency values should be sub-sampled to

remove_na_value

Should NA values be removed (default true)

remove_excluded

Should excluded values be removed (default true)

Value

The subset dataset, based on the values selected

Examples

vascr_subset(growth.df)
vascr_subset(growth.df, time = 40)
vascr_subset(growth.df, time = NULL)
 
vascr_subset(growth.df, unit = "Rb")
vascr_subset(growth.df, unit = "R")
vascr_subset(growth.df, well = "A1")

vascr_subset(growth.df, time = c(5,20))

Summarise a vascr data set down to a particular level

Description

Summarise a vascr data set down to a particular level

Usage

vascr_summarise(data.df, level = "wells")

Arguments

data.df

Data set to summarize

level

Level to summarise to, either "median_deviation", "ANOVA", "summary", "experiment" or "wells"

Value

The summarized data set

Examples

rbgrowth.df = vascr_subset(growth.df, unit = "Rb")

vascr_summarise(rbgrowth.df, level = "summary")
vascr_summarise(rbgrowth.df, level = "experiment")
vascr_summarise(rbgrowth.df, level = "wells")

Set a particular time point as 0 in a vascr dataset

Description

Allows the user to change the time designated as zero to allow clearer plotting of treatments

Usage

vascr_zero_time(data.df, time = 0)

Arguments

data.df

A vascr dataset

time

The time to be set to 0

Value

An adjusted vascr dataset

Examples

vascr_zero_time(growth.df, 50)

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