Package 'HaDeX2'

Description

The HaDeX2 package is a toolbox for the analysis of HDX-MS data.

Author(s)

Weronika Puchala, Michal Burdukiewicz.

See Also

Useful links:

• https://hadexversum.github.io/HaDeX2/

Description

Returns relation with confidence limits for each peptide.

Usage

add_stat_dependency(
  calc_dat,
  confidence_level = 0.98,
  theoretical = FALSE,
  fractional = TRUE
)

Arguments

Details

This function checks if the values are statistically significant based on provided criteria using Houde test.

Value

calc_dat extended by column specifying if given peptide is relevant in given confidence limit. The value of the confidence limit is added as an attribute - as well as parameters used to calculate (theoretical/fractional).

Examples

calc_dat <- calculate_diff_uptake(alpha_dat)
result <- add_stat_dependency(calc_dat)
head(result)

Description

Originally published in: Bondarchuk, T. V., Shalak, V. F., Lozhko, D. M., Fatalska, A., Szczepanowski, R. H., Liudkovska, V., Tsuvariev, O. Y., Dadlez, M., El’skaya, A. V., & Negrutskii, B. S. (2022). Quaternary organization of the human eEF1B complex reveals unique multi-GEF domain assembly. Nucleic Acids Research, 50(16), 9490–9504. <doi:/10.1093/nar/gkac685>

Author(s)

Bondarchuk, T. V., Shalak, V. F., Lozhko, D. M., Fatalska, A., Szczepanowski, R. H., Liudkovska, V., Tsuvariev, O. Y., Dadlez, M., El’skaya, A. V., & Negrutskii, B. S.

References

doi:10.1093/nar/gkac685

Description

Function aggregates the differential deuterium uptake values from peptide level into single-amino resolution using 'weighted approach' (defined in 'vignette("datafiles"))'. For visualization use plot_aggregated_uptake

Usage

calculate_aggregated_diff_uptake(diff_uptake_dat, time_t)

Arguments

Value

a data.frame object

Examples

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
calculate_aggregated_diff_uptake(diff_uptake_dat, time_t = 5)

Description

Function aggregates peptide-level information into residue level. Significance method indicates if the difference is significant or not - if the number of significant peptides over this residue is bigger than the number of insignificant.

Usage

calculate_aggregated_test_results(
  p_diff_uptake_conf_dat,
  method = c("significance", "weiss"),
  time_t = 1,
  skip_amino = 1
)

Arguments

Details

Only peptides without modification are aggregated.

Value

a data.frame object

See Also

read_hdx

Examples

p_diff_uptake_dat <- create_p_diff_uptake_dataset(alpha_dat)
p_diff_uptake_conf_dat <- create_p_diff_uptake_dataset_with_confidence(p_diff_uptake_dat)
calculate_aggregated_test_results(p_diff_uptake_conf_dat, method = "significance")
calculate_aggregated_test_results(p_diff_uptake_conf_dat, method = "weiss")

Description

Function aggregates the deuterium uptake values from peptide level into single-amino resolution using 'weighted approach' (defined in 'vignette("datafiles"))'. For visualization use plot_aggregated_uptake

Usage

calculate_aggregated_uptake(
  kin_dat,
  state = unique(kin_dat[["State"]])[1],
  time_t
)

Arguments

Value

a data.frame object

Examples

# disabled due to long execution time 

kin_dat <- create_uptake_dataset(alpha_dat, states = "Alpha_KSCN")
head(create_aggregated_uptake_dataset(kin_dat))

Description

Calculates area under the deuterium uptake curve

Usage

calculate_auc(
  uptake_dat,
  protein = uptake_dat[["Protein"]][1],
  state = uptake_dat[["State"]][1],
  preserve_values = FALSE
)

Arguments

Details

The AUC is calculated on the data normalized to unit square by division by maximum values of exposure time and deuterium uptake, respectively.

Value

a data.frame object

See Also

read_hdx create_uptake_dataset

Examples

uptake_dat <- create_uptake_dataset(alpha_dat)
head(calculate_auc(uptake_dat))

Description

Calculates back-exchange for a state

Usage

calculate_back_exchange(
  dat,
  protein = dat[["Protein"]][1],
  states = unique(dat[["State"]]),
  time_100 = max(dat[["Exposure"]])
)

Arguments

Details

Back-exchange is a reverse exchange phenomenon, important to acknowledge when working with HDX data. This function calculates back-exchange values for one biological state of the selected protein. For visualization of back-exchange data use plot_coverage_heatmap with displayed value specified as 'back-exchange'. For the definition of back-exchange see the 'vignette("datafiles")'.

Value

a data.frame object

See Also

read_hdx plot_coverage_heatmap

Examples

head(calculate_back_exchange(alpha_dat))

Description

Calculates confidence limit values for prepared provided, based on chosen parameters.

Usage

calculate_confidence_limit_values(
  diff_uptake_dat,
  confidence_level = 0.98,
  theoretical = FALSE,
  fractional = TRUE,
  n_rep = NULL
)

Arguments

Details

Function calculate_confidence_limit_values calculates confidence limit using Houde test. The confidence limits are calculated on whole provided dataset. If the user wishes to calculate confidence limit for one, two or more time points, the provided data should be adjusted accordingly.

Value

range of confidence limit interval

References

Houde, D., Berkowitz, S.A., and Engen, J.R. (2011). The Utility of Hydrogen/Deuterium Exchange Mass Spectrometry in Biopharmaceutical Comparability Studies. J Pharm Sci 100, 2071–2086.

See Also

read_hdx calculate_diff_uptake create_diff_uptake_dataset

Examples

diff_uptake_dat <- calculate_diff_uptake(alpha_dat)
calculate_confidence_limit_values(diff_uptake_dat)

Description

Calculates differential deuterium uptake between two selected biological states.

Usage

calculate_diff_uptake(
  dat,
  protein = unique(dat[["Protein"]][1]),
  states = unique(dat[["State"]])[1:2],
  time_0 = min(dat[["Exposure"]]),
  time_t = unique(dat[["Exposure"]])[3],
  time_100 = max(dat[["Exposure"]]),
  deut_part = 0.9
)

Arguments

Details

Function calculate_diff_uptake calculates differential values based on provided criteria for peptides for chosen protein in selected states. The methods of calculation of deuterium uptake difference, fractional deuterium uptake difference with respect to minimal/maximal exchange controls or theoretical tabular values are thoroughly described in the 'Data processing' article, as well as law of propagation of uncertainty, used to calculate uncertainty.

Value

a data.frame object.

See Also

read_hdx calculate_state_uptake

Examples

diff_dat <- calculate_diff_uptake(alpha_dat)
head(diff_dat)

Description

Calculate the measured mass (with the uncertainty of the measurement) as aggregated data from the replicates of the experiment.

Usage

calculate_exp_masses(dat)

Arguments

Details

Each measurement is repeated at least three times to obtain reliable result and to calculate uncertainty of the measurement. For more information on how the data is aggregated or how the uncertainty is calculated, see the documentation.

Value

a data.frame object.

See Also

read_hdx calculate_exp_masses_per_replicate calculate_state_uptake

Examples

calculate_exp_masses(alpha_dat)

Description

Calculate the measured mass from partial results, per each replicate of the experiment.

Usage

calculate_exp_masses_per_replicate(dat)

Arguments

Details

Each replicate of the experiment generates measurements of the mass for obtained charge values for the peptide. This is an effect of the properties of mass spectrometry, that measures the mass to charge ratio (learn more about Mass Spectrometry in the documentation). The possible charge values depend on the sequence of the peptide. The separate measurement (for each replicate in given state in given time point) can be distinguished by the 'File' value.

Value

a data.frame object.

See Also

read_hdx calculate_exp_masses calculate_state_uptake

Examples

head(calculate_exp_masses_per_replicate(alpha_dat))

Description

Calculate kinetics of the hydrogen-deuteration exchange for given peptide in given state.

Usage

calculate_kinetics(
  dat,
  protein = dat[["Protein"]][1],
  sequence = dat[["Sequence"]][1],
  state = dat[["State"]][1],
  start = dat[["Start"]][1],
  end = dat[["End"]][1],
  time_0 = min(dat[["Exposure"]]),
  time_100 = max(dat[["Exposure"]]),
  deut_part = 0.9
)

Arguments

Details

The function calculates deuteration data for all available data points for given peptide in chosen biological state.. All four variants (relative & theoretical combinations) of deuterium uptake computations are supported. Manual correction of percentage of deuterium the protein was exposed to during the exchange in theoretical calculations is provided. To visualize obtained data we recommend using plot_uptake_curve function. The first version doesn't support filled Modification and Fragment columns. IMPORTANT! The kinetic data is often described as deuterium uptake curve data. We use this terms interchangeable.

Value

a data.frame object.

See Also

read_hdx calculate_state_uptake plot_uptake_curve

Examples

# by default: for the first peptide
calculate_kinetics(alpha_dat)

Description

Calculate the mass of the singly charged monoisotopic (or not) molecular ion of for given peptide.

Usage

calculate_MHP(Sequence, mono = FALSE)

Arguments

Details

This function calculates the mass of the singly charged monoisotopic (or not) molecular ion for given peptide. It is the sum of the residue masses plus the masses of the terminating group (H and OH). The source of the masses can be found here: http://www.matrixscience.com/help/aa_help.html. Keep in mind that this function returns the value of an unmodified peptide.

Value

vector of numeric MHP values of provided Sequences

See Also

read_hdx calculate_state_uptake

Examples

calculate_MHP("CHERICHERILADY")
calculate_MHP("CHERICHERILADY", mono = TRUE)

Description

Create p-value dataset

Usage

calculate_p_value(
  dat,
  protein = unique(dat[["Protein"]])[1],
  state_1 = unique(dat[["State"]])[1],
  state_2 = unique(dat[["State"]])[2],
  p_adjustment_method = "none",
  confidence_level = 0.98
)

Arguments

Details

This function calculates P-value based on the supplied data. Unpaired t-Student test (with supplied parameters) is used to establish if the null hypothesis (there is no difference between measured mass values between two selected biological states) can be rejected, based on the experimental mass values from replicates of the experiment - for peptide in given time point of measurement. For the peptides that have only one replicate of the measurement (in any state) the P-value cannot be calculated and is assigned with NA value.

Value

a data.frame object.

See Also

read_hdx calculate_exp_masses_per_replicate plot_volcano create_diff_uptake_dataset create_p_diff_uptake_dataset

Examples

p_dat <- calculate_p_value(alpha_dat)
head(p_dat)

Description

Calculate kinetics of the hydrogen-deuteration exchange for given peptide in multiple biological states.

Usage

calculate_peptide_kinetics(
  dat,
  protein = dat[["Protein"]][1],
  sequence = dat[["Sequence"]][1],
  states = unique(dat[["State"]]),
  start = dat[["Start"]][1],
  end = dat[["End"]][1],
  time_0 = min(dat[["Exposure"]]),
  time_100 = max(dat[["Exposure"]]),
  deut_part = 0.9
)

Arguments

Details

Function calculate_peptide_kinetics calculates kinetic data for chosen peptide in chosen biological states. It is a wrapper for calculate_kinetics but for multiple states. The output of this function can be visualized using plot_uptake_curve. IMPORTANT! The kinetic data is often described as deuterium uptake curve data. We use this terms interchangeable.

Value

a data.frame object.

See Also

calculate_kinetics calculate_state_uptake plot_uptake_curve

Examples

# by default calculated for the first peptide from the peptide pool
calculate_peptide_kinetics(alpha_dat)

Description

Calculates deuteration uptake based on supplied parameters.

Usage

calculate_state_uptake(
  dat,
  protein = unique(dat[["Protein"]])[1],
  state = unique(dat[["State"]])[1],
  time_0 = min(dat[dat[["Exposure"]] > 0, ][["Exposure"]]),
  time_t = unique(dat[["Exposure"]])[3],
  time_100 = max(dat[["Exposure"]]),
  deut_part = 0.9
)

Arguments

Details

The function calculate_state_uptake calculates deuterium uptake (in different forms) for all of the peptides in given protein in given state based on supplied parameters: 'time_0', 'time_100' and 'time_t'. All four variants (fractional) are supplied (mean values and uncertainty). Manual correction of percentage of deuterium the protein was exposed to during the exchange in theoretical calculations is provided.

Methods of calculation and uncertainty are profoundly discussed in the vignette.

Value

a data.frame object

See Also

read_hdx create_uptake_dataset calculate_confidence_limit_values add_stat_dependency

Examples

head(calculate_state_uptake(alpha_dat))

Description

This is a wrapper function for calculate_aggregated_diff_uptake, which calculates aggregated differential uptake for only one time point. This function returns values for all time points from 'diff_uptake_dat'.

Usage

create_aggregated_diff_uptake_dataset(diff_uptake_dat)

Arguments

Value

a data.frame object

Examples

# disabled due to long execution time 

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
head(create_aggregated_diff_uptake_dataset(diff_uptake_dat))

Description

This is a wrapper function for calculate_aggregated_uptake, which calculates aggregated uptake for only one time point. This function returns values for all time points from 'kin_dat'.

Usage

create_aggregated_uptake_dataset(kin_dat)

Arguments

Value

a data.frame object

Examples

# disabled due to long execution time 

kin_dat <- create_uptake_dataset(alpha_dat, states = "Alpha_KSCN")
create_aggregated_uptake_dataset(kin_dat)

Description

This function adds selected experimental maximal exchange control as a measurement for all biological states.

Usage

create_control_dataset(
  dat,
  control_protein = dat[["Protein"]][1],
  control_state = dat[["State"]][1],
  control_exposure = max(dat[["Exposure"]])
)

Arguments

Details

Function create_control_dataset creates a dataset (similar to the output of read_hdx function), with maximal exchange control for all the states, based on provided parameters. The other functions are operating within a state, so the control is prepared for each state. The chosen maximal exchange control is distinguishable by the value '99999' in 'Exposure' control.

Value

a data.frame object.

See Also

read_hdx calculate_state_uptake

Examples

head(create_control_dataset(alpha_dat))

Description

Calculates differential deuterium uptake values between two states.

Usage

create_diff_uptake_dataset(
  dat,
  protein = unique(dat[["Protein"]])[1],
  state_1 = unique(dat[["State"]])[1],
  state_2 = unique(dat[["State"]])[2],
  time_0 = min(dat[["Exposure"]]),
  time_100 = max(dat[["Exposure"]]),
  deut_part = 0.9
)

Arguments

Details

The function create_diff_uptake_dataset generates a dataset with differential values between given biological states (state_1 - state_2). For each peptide of chosen protein for time points of measurement between minimal and maximal control time points of measurement deuterium uptake difference, fractional deuterium uptake difference with respect to controls or theoretical tabular values are calculated, with combined and propagated uncertainty. Each peptide has an ID, based on its start position. Function output can be visualized as a differential (Woods) plot, butterfly differential plot or chiclet differential plot.

Value

a data.frame object.

See Also

read_hdx calculate_diff_uptake plot_differential_butterfly plot_differential_chiclet plot_differential

Examples

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
head(diff_uptake_dat)

Description

Generates the data set of deuterium uptake between selected time points based on supplied peptide list.

Usage

create_kinetic_dataset(
  dat,
  peptide_list,
  protein = dat[["Protein"]][1],
  time_0 = min(dat[["Exposure"]]),
  time_100 = max(dat[["Exposure"]]),
  deut_part = 0.9
)

Arguments

Details

This is a wrapper for calculate_kinetics, but for the peptide list instead of one peptide.

Value

a data.frame object.

See Also

calculate_kinetics calculate_state_uptake plot_uptake_curve

Examples

peptide_list <- data.frame(Sequence = c("GFGDLKSPAGL", "FGDLKSPAGL"), 
                           state = c("ALPHA_Gamma", "ALPHA_Gamma"), 
                           start = c(1, 2), end = c(11, 11))
create_kinetic_dataset(alpha_dat, peptide_list)

Description

Generates the data of frequency of overlap of each amino in the protein sequence.

Usage

create_overlap_distribution_dataset(
  dat,
  protein = dat[["Protein"]][1],
  state = dat[["State"]][1],
  start = min(dat[["Start"]]),
  end = max(dat[["End"]]),
  protein_sequence = reconstruct_sequence(dat)
)

Arguments

Details

This data frame presents how many times (by how many peptides) a amino position in protein sequence is covered. This data is available in the GUI.

Value

a data.frame object.

See Also

read_hdx reconstruct_sequence

Examples

create_overlap_distribution_dataset(alpha_dat)

Description

Creates differential deuterium uptake dataset with P-value from t-Student test for selected two biological states.

Usage

create_p_diff_uptake_dataset(
  dat,
  diff_uptake_dat = NULL,
  protein = unique(dat[["Protein"]])[1],
  state_1 = unique(dat[["State"]])[1],
  state_2 = unique(dat[["State"]])[2],
  p_adjustment_method = "none",
  confidence_level = 0.98,
  time_0 = min(dat[["Exposure"]]),
  time_100 = max(dat[["Exposure"]]),
  deut_part = 0.9
)

Arguments

Details

For peptides in all of the time points of measurement (except for minimal and maximal exchange control) the deuterium uptake difference between state_1 and state_2 is calculated, with its uncertainty (combined and propagated as described in 'Data processing' article). For each peptide in time point the P-value is calculated using unpaired t-test. The deuterium uptake difference is calculated as the difference of measured masses in a given time point for two states. The tested hypothesis is that the mean masses for states from the replicates of the experiment are similar. The P-values indicates if the null hypothesis can be rejected - rejection of the hypothesis means that the difference between states is statistically significant at provided confidence level. The P-values can be adjusted using the provided method.

Value

a data.frame object with calculated deuterium uptake difference in different forms with their uncertainty, P-value and -log(P-value) for the peptides from the provided data.

References

Hageman, T. S. & Weis, D. D. Reliable Identification of Significant Differences in Differential Hydrogen Exchange-Mass Spectrometry Measurements Using a Hybrid Significance Testing Approach. Anal Chem 91, 8008–8016 (2019).

See Also

read_hdx calculate_exp_masses_per_replicate

Examples

p_diff_uptake_dat <- create_p_diff_uptake_dataset(alpha_dat)
head(p_diff_uptake_dat)

Description

Create differential dataset with statistical validity

Usage

create_p_diff_uptake_dataset_with_confidence(
  p_diff_uptake_dat,
  houde_interval = NULL,
  houde_interval_times = NULL,
  theoretical = FALSE,
  fractional = FALSE
)

Arguments

Details

Function provides additional information on statistical relevance based on supplied data.

Value

a data.frame object.

See Also

read_hdx create_p_diff_uptake_dataset calculate_confidence_limit_values

Examples

p_diff_uptake_dat <- create_p_diff_uptake_dataset(alpha_dat)
p_diff_uptake_dat_confidence <- create_p_diff_uptake_dataset_with_confidence(p_diff_uptake_dat)
head(p_diff_uptake_dat_confidence)

Description

Checks how the uncertainty changes in a function of maximal exchange control time of measurement.

Usage

create_quality_control_dataset(
  dat,
  protein = dat[["Protein"]][1],
  state_1 = unique(dat[["State"]])[1],
  state_2 = unique(dat[["State"]])[2],
  time_t = unique(dat[["Exposure"]])[2],
  time_0 = min(dat[["Exposure"]]),
  deut_part = 0.9
)

Arguments

Details

The function calculates mean uncertainty of all peptides and its uncertainty (standard error) based on given 'time_0' and 'time_t' as a function of 'time_100'. Both theoretical and experimental results for each state and their difference are supplied for comparison but only experimental calculations depends on 'time_100' variable. The results are either in form of fractional or absolute values depending on the 'fractional' parameter supplied by the user. This data can be useful for general overview of the experiment and analyze of the chosen time parameters.

Value

data.frame object with mean uncertainty per different 'time_100' value. The values are shown as percentages.

See Also

read_hdx calculate_state_uptake plot_quality_control show_quality_control_data

Examples

create_quality_control_dataset(alpha_dat)

Description

Create replicate data set suitable for replicate histogram, for one or multiple time points of measurement.

Usage

create_replicate_dataset(
  dat,
  time_t = NULL,
  protein = unique(dat[["Protein"]])[1],
  state = dat[["State"]][1]
)

Arguments

Details

The function create_replicate_dataset creates a dataset with information about how many replicates are for peptides in specific state in time points of measurement.

Value

a data.frame object.

See Also

plot_replicate_histogram show_replicate_histogram_data

Examples

create_replicate_dataset(alpha_dat)

Description

Calculates deuterium uptake values for selected biological states in selected time point of measurements.

Usage

create_state_comparison_dataset(
  dat,
  protein = unique(dat[["Protein"]])[1],
  states = unique(dat[["State"]]),
  time_0 = min(dat[["Exposure"]]),
  time_t = unique(dat[["Exposure"]])[3],
  time_100 = max(dat[["Exposure"]]),
  deut_part = 0.9
)

Arguments

Details

Function create_state_comparison_dataset is a wrapper for calculate_state_uptake function, calls this function for all (default) or chosen states in states vector.

Value

a data.frame object.

See Also

read_hdx calculate_state_uptake

Examples

comparison_dat <- create_state_comparison_dataset(alpha_dat)
head(comparison_dat)

Description

Calculates deuterium uptake values for one biological state.

Usage

create_state_uptake_dataset(
  dat,
  protein = unique(dat[["Protein"]])[1],
  state = (dat[["State"]])[1],
  time_0 = min(dat[dat[["Exposure"]] > 0, ][["Exposure"]]),
  time_100 = max(dat[["Exposure"]]),
  deut_part = 0.9
)

Arguments

Details

The function create_uptake_dataset generates a dataset with deuterium uptake values in different forms. For each peptide in chosen protein in chosen state for time points of measurement between minimal and maximal control time points of measurement deuterium uptake, fractional deuterium uptake with respect to controls or theoretical tabular values are calculated, with combined and propagated uncertainty. Each peptide has an ID, based on its start position. This data can be presented in a form of comparison plot, butterfly plot or chiclet plot.

Value

a data.frame object.

See Also

read_hdx calculate_state_uptake

Examples

state_uptake_dat <- create_state_uptake_dataset(alpha_dat)
head(state_uptake_dat)

Description

Calculates deuterium uptake values for selected biological states in multiple time points of measurements.

Usage

create_uptake_dataset(
  dat,
  protein = unique(dat[["Protein"]])[1],
  states = unique(dat[["State"]]),
  time_0 = min(dat[["Exposure"]]),
  time_100 = max(dat[["Exposure"]]),
  deut_part = 0.9
)

Arguments

Details

Function create_uptake_dataset generates a dataset with deuterium uptake values in different forms. For each peptide in chosen protein in chosen states for time points of measurement between minimal and maximal control time points of measurement deuterium uptake, fractional deuterium uptake with respect to controls or theoretical tabular values are calculated, with combined and propagated uncertainty. Each peptide has an ID, based on its start position. This function is a wrapper for create_state_uptake_dataset but for multiple states. The output of this function can be presented in a form of comparison plot.

Value

a data.frame object.

See Also

read_hdx calculate_state_uptake create_state_uptake_dataset

Examples

uptake_dat <- create_uptake_dataset(alpha_dat, states = c("Alpha_KSCN", "ALPHA_Gamma"))
head(uptake_dat)

Description

Calculates the number of replicates from the experimental data.

Usage

get_n_replicates(dat, protein = dat[["Protein"]][1])

Arguments

Details

Calculate the number of replicates of experiment.

Value

a numeric value.

See Also

read_hdx

Examples

get_n_replicates(alpha_dat)

Description

Gets the peptide sequence based on selected parameters (start and end position, modification).

Usage

get_peptide_sequence(
  dat,
  protein = dat[["Protein"]][1],
  start,
  end,
  modification = FALSE
)

Arguments

Details

Function returns peptide sequence for selected parameters. Peptide sequence is often required to properly identify peptide of interest, and to avoid mistakes sequence is returned by the function. Moreover, function uses the modification value to select peptide sequence.

Value

a character value.

See Also

read_hdx

Examples

get_peptide_sequence(alpha_dat, start = 1, end = 11)

Description

Calculate protein coverage by the peptides in selected biological state or states.

Usage

get_protein_coverage(
  dat,
  protein = dat[["Protein"]][1],
  states = unique(dat[["State"]]),
  protein_length = NULL
)

Arguments

Details

Function get_protein_coverage calculates the percentage coverage of the protein sequence, rounded to two decimal places.

Value

a numeric percentage value (rounded to two decimal places).

See Also

read_hdx

Examples

get_protein_coverage(alpha_dat)
get_protein_coverage(alpha_dat, protein_length = 230)

Description

Calculates the protein redundancy in the whole experiment (all biological states).

Usage

get_protein_redundancy(dat, protein_length = NULL)

Arguments

Details

Function get_protein_redundancy calculates the redundancy of the protein, based on provided experimental data.

Value

a numeric value.

See Also

read_hdx

Examples

get_protein_redundancy(alpha_dat)

Description

Get list of peptides with their standard deviation.

Usage

get_replicate_list_sd(
  dat,
  protein = dat[["Protein"]][1],
  state = dat[["State"]][1],
  time_t = unique(dat[["Exposure"]])[3]
)

Arguments

Details

Function gets the pepitde list in selected state with their standard deviation of measurement, calculated from the technical replicates. It is used for selection for measurement variability plot.

Value

a data.frame object.

See Also

create_replicate_dataset

Examples

get_replicate_list_sd(alpha_dat)

Description

Get residue positions

Usage

get_residue_positions(dat)

Arguments

Details

Prepares data table for high-resolution values. It creates a long data frame with each position in the sequence accompanied by the amino acid placed in this position.

Value

a data.frame object.

Examples

# disabled due to long execution time 
get_residue_positions(alpha_dat)

Description

This function provides a set of color codes associated with aggregated values to be presented on 3D structure.

Usage

get_structure_color(
  aggregated_dat,
  differential = FALSE,
  fractional = TRUE,
  theoretical = FALSE,
  time_t
)

Arguments

Value

a list

Examples

# disabled due to long execution time 

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
diff_aggregated_dat <- create_aggregated_diff_uptake_dataset(diff_uptake_dat)
get_structure_color(diff_aggregated_dat, 
                    differential = TRUE,
                    time_t = 1)

Description

Shows how to launch graphical user interface from HaDeXGUI package. If the GUI package is not installed, it asks user whether to install it.

Usage

HaDeX_GUI()

Value

No return value, called for side effects

Warning

Any ad-blocking software may cause malfunctions.

Description

This function HaDeXifies plot. It adds HaDeX logo and ggplot theme.

Usage

HaDeXify(plt)

Arguments

Details

Function adds the logo of HaDeX package in the left down corner of the plot and the HaDeX theme.

Value

a ggplot object.

See Also

read_hdx plot_differential plot_butterfly

Examples

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
HaDeXify(plot_differential(diff_uptake_dat))

Description

Installs GUI package from GitHub

Usage

install_GUI()

Value

No return value, called for side effects

Description

Indicates presence or absence of HaDeXGUI package.

Usage

is_GUI_installed()

Value

logical value indicating availability of GUI package

Description

Plots aggregated uptake difference

Usage

plot_aggregated_differential_uptake(
  aggregated_diff_dat,
  fractional = TRUE,
  theoretical = FALSE,
  time_100 = max(unique(aggregated_diff_dat[["Exposure"]])),
  panels = FALSE,
  interactive = FALSE
)

Arguments

Value

a ggplot object

See Also

create_diff_uptake_dataset create_aggregated_diff_uptake_dataset

Examples

# disabled due to long execution time 

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
aggregated_diff_dat <- create_aggregated_diff_uptake_dataset(diff_uptake_dat)
plot_aggregated_differential_uptake(aggregated_diff_dat, panels = FALSE)
plot_aggregated_differential_uptake(aggregated_diff_dat, fractional = FALSE, 
                                    theoretical = TRUE, panels = FALSE)
plot_aggregated_differential_uptake(aggregated_diff_dat, theoretical = TRUE, 
                                    panels = TRUE)

Description

Plots aggregated uptake

Usage

plot_aggregated_uptake(
  aggregated_dat,
  fractional = TRUE,
  theoretical = FALSE,
  time_100 = max(unique(aggregated_dat[["Exposure"]])),
  panels = FALSE,
  interactive = FALSE
)

Arguments

Value

a ggplot object

Examples

# disabled due to long execution time 

kin_dat <- create_uptake_dataset(alpha_dat, states = "Alpha_KSCN")
aggregated_dat <- create_aggregated_uptake_dataset(kin_dat)
plot_aggregated_uptake(aggregated_dat, panels = FALSE)
plot_aggregated_uptake(aggregated_dat, fractional = FALSE, panels = FALSE)
plot_aggregated_uptake(aggregated_dat, fractional = FALSE, theoretical = TRUE, panels = TRUE)

Description

Function plots the aggregated data (either one state deuterium uptake or differential deuterium uptake) on the 3d structure.

Usage

plot_aggregated_uptake_structure(
  aggregated_dat,
  differential = FALSE,
  fractional = TRUE,
  theoretical = FALSE,
  time_t,
  pdb_file_path
)

Arguments

Value

a r3dmol object.

Examples

library(shiny)
# disabled due to its long time and producing 3rdmol object

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
diff_aggregated_dat <- create_aggregated_diff_uptake_dataset(diff_uptake_dat)
pdb_file_path <- system.file(package = "HaDeX2", "HaDeX/data/Model_eEF1Balpha.pdb")

plot_aggregated_uptake_structure(diff_aggregated_dat,
                                differential = TRUE,
                                 time_t = 1,
                                 pdb_file_path = pdb_file_path)

kin_dat <- create_uptake_dataset(alpha_dat, states = "Alpha_KSCN" )
aggregated_dat <- create_aggregated_uptake_dataset(kin_dat)
plot_aggregated_uptake_structure(aggregated_dat,
                                 differential = FALSE,
                                 time_t = 1,
                                 pdb_file_path = pdb_file_path)

Description

Generates amino distribution based on the protein sequence and shows if the amino acid is hydrophobic or hydrophylic.

Usage

plot_amino_distribution(
  position_in_sequence,
  hydro_properties,
  protein,
  charge_colors,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

The data for this function is not packaged yet.

Value

a ggplot object.

Description

Butterfly plot of deuterium uptake values in time for one biological state.

Usage

plot_butterfly(
  uptake_dat,
  theoretical = FALSE,
  fractional = FALSE,
  uncertainty_type = "ribbon",
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

Function plot_butterfly generates butterfly plot based on provided data and parameters. On X-axis there is peptide ID. On the Y-axis there is deuterium uptake in chosen form. Data from multiple time points of measurement is presented.

Value

a ggplot object.

See Also

create_state_uptake_dataset

Examples

state_uptake_dat <- create_state_uptake_dataset(alpha_dat)
plot_butterfly(state_uptake_dat)

Description

Chiclet plot of deuterium uptake values in time for one biological state.

Usage

plot_chiclet(
  uptake_dat,
  theoretical = FALSE,
  fractional = FALSE,
  show_uncertainty = FALSE,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

Function plot_chiclet produces a chiclet plot based on the same dataset as butterfly plot, as it is the different form of presenting the same data. On X-axis there is a peptide ID. On Y-axis are time points of measurement. Each tile for a peptide in time has a color value representing the deuterium uptake, in a form based on provided criteria (e.q. fractional). Each tile has a plus sign, which size represent the uncertainty of measurement for chosen value.

Value

a ggplot object.

See Also

create_state_uptake_dataset

Examples

state_uptake_dat <- create_state_uptake_dataset(alpha_dat)
plot_chiclet(state_uptake_dat)

Description

Plot the peptide coverage of the protein sequence

Usage

plot_coverage(
  dat,
  protein = dat[["Protein"]][1],
  states = NULL,
  show_blanks = TRUE,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

The function plot_coverage generates sequence coverage plot based on experimental data for selected protein in selected biological states. Only non-duplicated peptides are shown on the plot, next to each other.

The aim of this plot is to see the dependence between position of the peptide on the protein sequence. Their position on y-axis does not contain any information.

Value

a ggplot object

See Also

read_hdx plot_position_frequency

Examples

plot_coverage(alpha_dat)
plot_coverage(alpha_dat, show_blanks = FALSE)

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
plot_coverage(diff_uptake_dat)

Description

Coverage heatmap with color indicating specific value

Usage

plot_coverage_heatmap(
  x_dat,
  protein = x_dat[["Protein"]][1],
  state = NULL,
  value = NULL,
  time_t = NULL,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

Plots standard protein coverage but colored with desired value.

Value

a ggplot object

See Also

read_hdx plot_coverage

Examples

uptake_dat <- create_uptake_dataset(alpha_dat, states = "Alpha_KSCN")
plot_coverage_heatmap(uptake_dat)
plot_coverage_heatmap(x_dat = uptake_dat, value = "frac_deut_uptake", time_t = 0.167)
plot_coverage_heatmap(uptake_dat, value = "err_frac_deut_uptake", time_t = 0.167)

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
plot_coverage_heatmap(diff_uptake_dat)
plot_coverage_heatmap(diff_uptake_dat, value = "diff_frac_deut_uptake")
plot_coverage_heatmap(diff_uptake_dat, value = "diff_frac_deut_uptake", time_t = 0.167)
plot_coverage_heatmap(diff_uptake_dat, value = "err_diff_frac_deut_uptake", time_t = 0.167)

auc_dat <- calculate_auc(create_uptake_dataset(alpha_dat))
plot_coverage_heatmap(auc_dat, value = "auc")

bex_dat <- calculate_back_exchange(alpha_dat, state = "Alpha_KSCN")
plot_coverage_heatmap(bex_dat, value = "back_exchange")

Description

Woods plot of differential deuterium uptake values between two biological states in time point.

Usage

plot_differential(
  diff_uptake_dat = NULL,
  diff_p_uptake_dat = NULL,
  skip_amino = 0,
  time_t = NULL,
  theoretical = FALSE,
  fractional = FALSE,
  show_houde_interval = FALSE,
  hide_houde_insignificant = FALSE,
  show_tstud_confidence = FALSE,
  hide_tstud_insignificant = FALSE,
  confidence_level = 0.98,
  all_times = FALSE,
  line_size = 1.5,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

Function plot_differential presents provided data in a form of differential (Woods) plot. The plot shows difference in exchange for two biological states, selected in generation of dataset at one time point of measurement. On X-axis there is a position in a sequence, with length of a segment of each peptide representing its length. On Y-axis there is deuterium uptake difference in chosen form. Error bars represents the combined and propagated uncertainty. For Woods Plot there is available Houde test and t-Student test to see the statistically significant peptides. Selecting both of them simultaneously results in hybrid testing, as described in Weis et al. The statistically significant values are in color (red if the difference is positive, blue if negative), and the insignificant values are grey.

Value

a [ggplot2::ggplot()] object.

References

Hageman, T. S. & Weis, D. D. Reliable Identification of Significant Differences in Differential Hydrogen Exchange-Mass Spectrometry Measurements Using a Hybrid Significance Testing Approach. Anal Chem 91, 8008–8016 (2019).

See Also

create_diff_uptake_dataset calculate_diff_uptake show_diff_uptake_data

Examples

# disabled due to long execution time 

diff_uptake_dat <- calculate_diff_uptake(alpha_dat,  
                                         states = c("ALPHA_Gamma", "Alpha_KSCN"), time_t = 0.167)
plot_differential(diff_uptake_dat = diff_uptake_dat, time_t = 0.167) 
plot_differential(diff_uptake_dat = diff_uptake_dat, time_t = 0.167, show_houde_interval = TRUE) 
plot_differential(diff_uptake_dat = diff_uptake_dat, time_t = 0.167, skip_amino = 0) 
plot_differential(diff_uptake_dat = diff_uptake_dat, time_t = 0.167, line_size = 1) 
plot_differential(diff_uptake_dat = diff_uptake_dat, all_times = TRUE)
plot_differential(diff_uptake_dat = diff_uptake_dat, all_times = TRUE, show_houde_interval = TRUE)
plot_differential(diff_uptake_dat = diff_uptake_dat, all_times = TRUE, show_houde_interval = TRUE, 
                 hide_houde_insignificant = TRUE)

diff_p_uptake_dat <- create_p_diff_uptake_dataset(alpha_dat, state_1 = "Alpha_KSCN", 
                                                  state_2 = "ALPHA_Gamma")
plot_differential(diff_p_uptake_dat = diff_p_uptake_dat, all_times = TRUE, 
                  show_tstud_confidence = TRUE)
plot_differential(diff_p_uptake_dat = diff_p_uptake_dat, all_times = FALSE, 
                  time_t = 0.167, show_tstud_confidence = TRUE, show_houde_interval = TRUE)
plot_differential(diff_p_uptake_dat = diff_p_uptake_dat, show_tstud_confidence = TRUE, 
                  show_houde_interval = TRUE, all_times = FALSE)
plot_differential(diff_p_uptake_dat = diff_p_uptake_dat, show_tstud_confidence = TRUE, 
                  show_houde_interval = TRUE, all_times = FALSE, hide_houde_insignificant = TRUE)
plot_differential(diff_p_uptake_dat = diff_p_uptake_dat, show_tstud_confidence = TRUE, 
                  show_houde_interval = TRUE, all_times = FALSE, hide_houde_insignificant = TRUE, 
                  hide_tstud_insignificant = TRUE)

Description

Butterfly plot of differential deuterium uptake values between two biological states in time.

Usage

plot_differential_butterfly(
  diff_uptake_dat = NULL,
  diff_p_uptake_dat = NULL,
  theoretical = FALSE,
  fractional = FALSE,
  show_houde_interval = FALSE,
  show_tstud_confidence = FALSE,
  uncertainty_type = "ribbon",
  confidence_level = 0.98,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

Function plot_differential_butterfly generates differential butterfly plot based on provided data and parameters. On X-axis there is peptide ID. On the Y-axis there is deuterium uptake difference in chosen form. Data from multiple time points of measurement is presented. If chosen, there are confidence limits based on Houde test on provided confidence level.

Value

a [ggplot2::ggplot()] object.

References

Houde, D., Berkowitz, S.A., and Engen, J.R. (2011). The Utility of Hydrogen/Deuterium Exchange Mass Spectrometry in Biopharmaceutical Comparability Studies. J Pharm Sci 100, 2071–2086.

See Also

read_hdx create_diff_uptake_dataset calculate_diff_uptake

Examples

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
plot_differential_butterfly(diff_uptake_dat = diff_uptake_dat)
plot_differential_butterfly(diff_uptake_dat = diff_uptake_dat, show_houde_interval = TRUE)

diff_p_uptake_dat <- create_p_diff_uptake_dataset(alpha_dat)
plot_differential_butterfly(diff_p_uptake_dat = diff_p_uptake_dat, show_tstud_confidence = TRUE)

Description

Chiclet plot of differential deuterium uptake values between two biological states in time.

Usage

plot_differential_chiclet(
  diff_uptake_dat = NULL,
  diff_p_uptake_dat = NULL,
  theoretical = FALSE,
  fractional = FALSE,
  show_houde_interval = FALSE,
  show_tstud_confidence = FALSE,
  confidence_level = 0.98,
  show_uncertainty = FALSE,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

Function plot_differential_chiclet generates chiclet differential plot based on provided data and parameters. On X-axis there is a peptide ID. On Y-axis are time points of measurement. Each tile for a peptide in time has a color value representing the deuterium uptake difference between chosen states, in a form based on provided criteria (e.q. fractional). Each tile has a plus sign, which size represent the uncertainty of measurement for chosen value.

Value

a [ggplot2::ggplot()] object.

See Also

create_diff_uptake_dataset calculate_diff_uptake

Examples

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
plot_differential_chiclet(diff_uptake_dat)
plot_differential_chiclet(diff_uptake_dat, show_houde_interval = TRUE)

diff_p_uptake_dat <- create_p_diff_uptake_dataset(alpha_dat)
plot_differential_chiclet(diff_p_uptake_dat = diff_p_uptake_dat, 
                          show_tstud_confidence = TRUE)
plot_differential_chiclet(diff_p_uptake_dat = diff_p_uptake_dat, 
                          show_tstud_confidence = TRUE, show_houde_interval = TRUE)

Description

Differential uptake curve for one peptide between two biological states.

Usage

plot_differential_uptake_curve(
  diff_uptake_dat = NULL,
  diff_p_uptake_dat = NULL,
  sequence = NULL,
  theoretical = FALSE,
  fractional = FALSE,
  uncertainty_type = "ribbon",
  log_x = TRUE,
  show_houde_interval = FALSE,
  show_tstud_confidence = FALSE,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

This plot shows the differential deuterium uptake between two biological states for selected peptides in different time points. The possibility to plot multiple differences (between state and mutant) for the peptide will be added soon.

Value

a ggplot object.

See Also

read_hdx create_diff_uptake_dataset calculate_diff_uptake

Examples

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
plot_differential_uptake_curve(diff_uptake_dat = diff_uptake_dat, sequence = "GDLKSPAGL")

diff_p_uptake_dat <- create_p_diff_uptake_dataset(alpha_dat)
plot_differential_uptake_curve(diff_p_uptake_dat = diff_p_uptake_dat, 
                               sequence = "GDLKSPAGL", show_houde_interval = TRUE)
plot_differential_uptake_curve(diff_p_uptake_dat = diff_p_uptake_dat, 
                               sequence = "GDLKSPAGL", show_houde_interval = TRUE, 
                               show_tstud_confidence = TRUE)
plot_differential_uptake_curve(diff_p_uptake_dat = diff_p_uptake_dat, 
                               sequence = "GDLKSPAGL", show_tstud_confidence = TRUE)

Description

Manhattan plot with p-values from the t-Student test and peptide position.

Usage

plot_manhattan(
  p_dat,
  skip_amino = 0,
  plot_title = NULL,
  separate_times = TRUE,
  times = NULL,
  confidence_level = NULL,
  show_confidence_limit = TRUE,
  show_peptide_position = FALSE,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

The manhattan plot presents the P-values from t-student test, to see the regions of the protein with statistically significant changes between two biological states. On X-axis there is a position in a sequence, with length of a segment of each peptide representing its length. On Y-axis there is P-value from t-Student test.

Value

a ggplot object.

References

Hageman, T. S. & Weis, D. D. Reliable Identification of Significant Differences in Differential Hydrogen Exchange-Mass Spectrometry Measurements Using a Hybrid Significance Testing Approach. Anal Chem 91, 8008–8016 (2019).

See Also

read_hdx create_p_diff_uptake_dataset

Examples

p_dat <- create_p_diff_uptake_dataset(alpha_dat)
plot_manhattan(p_dat)
plot_manhattan(p_dat, separate_times = FALSE)
plot_manhattan(p_dat, show_peptide_position = TRUE, separate_times = FALSE)
plot_manhattan(p_dat, separate_times = FALSE, show_confidence_limit = FALSE)

Description

Generates overlapping peptide plot based on supplied data and parameters.

Usage

plot_overlap(dat, protein = dat[["Protein"]][1], state = dat[["State"]][1])

Arguments

Details

The overlap plot presents all the peptides in given state on the protein sequence. This plot is visible in GUI.

Value

a ggplot object.

See Also

read_hdx show_overlap_data

Examples

plot_overlap(alpha_dat)

Description

Generates overlap distribution plot based on supplied data and parameters.

Usage

plot_overlap_distribution(
  overlap_dist_dat,
  start = 1,
  end = max(overlap_dist_dat[["pos"]]),
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

This plot presents how many times (by how many peptides) a amino position in protein sequence is covered. This plot is visible in GUI.

Value

a ggplot object.

See Also

read_hdx reconstruct_sequence create_overlap_distribution_dataset

Examples

overlap_dist_dat <- create_overlap_distribution_dataset(alpha_dat)
plot_overlap_distribution(overlap_dist_dat)

Description

Plot the charge measurements from replicates for peptide in specific time point.

Usage

plot_peptide_charge_measurement(
  dat,
  protein = dat[["Protein"]][1],
  state = dat[["State"]][1],
  sequence = dat[["Sequence"]][1],
  time_t = unique(dat[["Exposure"]])[3]
)

Arguments

Details

This function shows the measurements of charge from different replicates for specific peptide in specific state in specific time point of measurement on the plot.

Value

a [ggplot2::ggplot()] object.

See Also

read_hdx show_peptide_charge_measurement

Examples

plot_peptide_charge_measurement(alpha_dat)

Description

Plot the mass measurements from replicates for peptide in specific time point.

Usage

plot_peptide_mass_measurement(
  dat,
  protein = dat[["Protein"]][1],
  state = dat[["State"]][1],
  sequence = dat[["Sequence"]][1],
  show_charge_values = TRUE,
  time_t = unique(dat[["Exposure"]])[3],
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

This function shows the measurements of mass from different replicates for specific peptide in specific state in specific time point of measurement on the plot. Moreover, on the plot is shown the average mass from the replicates, used later in calculations. The ribbon next to the dotted average mass indicates the uncertainty.

Value

a [ggplot2::ggplot()] object.

See Also

read_hdx calculate_exp_masses_per_replicate calculate_exp_masses calculate_state_uptake calculate_diff_uptake

Examples

plot_peptide_mass_measurement(alpha_dat, sequence = "FGSDDEEESEEAKRLRE")
plot_peptide_mass_measurement(alpha_dat, sequence = "FGSDDEEESEEAKRLRE", show_charge_values = FALSE)

Description

Plot the frequency of coverage for protein sequence

Usage

plot_position_frequency(
  dat,
  protein = dat[["Protein"]][1],
  state = dat[["State"]][1]
)

Arguments

Details

The function plot_position_frequency generates a histogram of the coverage frequency in selected biological states for selected protein. The position frequency plot presents how many times each position of the sequence is covered by different peptides.

Value

a ggplot object.

See Also

read_hdx plot_coverage

Examples

plot_position_frequency(alpha_dat)

Description

Generates quality control plot based on supplied data.

Usage

plot_quality_control(qc_dat)

Arguments

Details

This plot presents the mean uncertainty in function of selected maximal exchange control time of measurement. This plot is visible in GUI.

Value

a [ggplot2::ggplot()] object.

See Also

create_quality_control_dataset show_quality_control_data

Examples

qc_dat <- create_quality_control_dataset(alpha_dat)  
plot_quality_control(qc_dat)

Description

Plot histogram on number of replicates per peptide in one or multiple time point of measurement.

Usage

plot_replicate_histogram(
  rep_dat,
  time_points = FALSE,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

The function shows three versions of replicate histogram, based on supplied rep_dat and time_points. If time_points is selected, the histogram shows the number of replicates for time points of measurement, to spot if there were troubles with samples for specific time point of measurement. Then, on the X-axis is Exposure (in minutes) and on the Y-axis number of replicates. If time_points is not selected, on the X-axis there are peptide ID, and on the Y-axis there are numbers of replicates. If rep_dat contains data from one time point of measurement, the histogram colors reflect the number of replicates to highlight the outliers. If rep_dat contains multiple time point of measurement, the colors help to distinguish between them.

Value

a [ggplot2::ggplot()] object.

See Also

create_replicate_dataset show_replicate_histogram_data

Examples

rep_dat <- create_replicate_dataset(alpha_dat)
plot_replicate_histogram(rep_dat)

plot_replicate_histogram(rep_dat, time_points = TRUE)

rep_dat <- create_replicate_dataset(alpha_dat, time_t = 0.167)
plot_replicate_histogram(rep_dat)

Description

Plot the mass uptake curve for selected peptide to see the difference between replicates.

Usage

plot_replicate_mass_uptake(
  dat,
  protein = dat[["Protein"]][1],
  state = dat[["State"]][1],
  sequence = dat[["Sequence"]][1],
  aggregated = FALSE,
  log_x = TRUE,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

The function plot_replicate_mass_uptake generates a plot showing the mass uptake for selected protein in replicates of the experiments. The values can be presented in two ways: as aggregated values for each replicate, or before aggregation - measured values for charge values within a replicate. The mass uptake is generated by subtracting the MHP mass of a peptide from measured mass and the mass uptake is presented in Daltons.

Value

a ggplot object.

See Also

read_hdx calculate_exp_masses_per_replicate

Examples

plot_replicate_mass_uptake(alpha_dat)
plot_replicate_mass_uptake(alpha_dat, aggregated = TRUE)

Description

Comparison plot of deuterium uptake values in time point for biological states.

Usage

plot_state_comparison(
  uptake_dat,
  skip_amino = 0,
  theoretical = FALSE,
  fractional = FALSE,
  line_size = 1.5,
  all_times = FALSE,
  time_t = NULL,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

The function plot_state_comparison generates a comparison plot, presenting deuterium uptake values of peptides from selected protein in selected biological states at one time point of measurement at once. On X-axis there is a position in a sequence, with length of a segment of each peptide representing its length. On Y-axis there is deuterium uptake in selected form. Error bars represents the combined and propagated uncertainty.

Value

a ggplot object

See Also

read_hdx calculate_state_uptake

Examples

uptake_dat <- calculate_state_uptake(alpha_dat)
plot_state_comparison(uptake_dat)

plot_state_comparison(uptake_dat, all_times = TRUE)
plot_state_comparison(uptake_dat, fractional = TRUE, all_times = TRUE)

Description

Plot the uncertainty of the mass measurements - for aggregated data or before aggregation - to see if there is a region with uncertainty higher than acceptable

Usage

plot_uncertainty(
  dat,
  protein = dat[["Protein"]][1],
  state = dat[["State"]][1],
  skip_amino = 0,
  aggregated = TRUE,
  separate_times = TRUE,
  show_threshold = TRUE,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

The function plot_uncertainty generates a plot of uncertainty of mass measurement of each peptide from selected protein in selected biological state. The values can be presented in two ways: as aggregated values for each replicate, or before aggregation - measured values for charge values within a replicate. On X-axis there is a position in a sequence, with length of a segment of each peptide representing its length. On Y-axis there is uncertainty of the measurement in Daltons. The threshold is set to 1 Da, as this value is associated with exchange.

Value

a ggplot object.

See Also

read_hdx calculate_exp_masses

Examples

plot_uncertainty(alpha_dat)
plot_uncertainty(alpha_dat, aggregated = FALSE)
plot_uncertainty(alpha_dat, aggregated = FALSE, separate_times = FALSE)
plot_uncertainty(alpha_dat, skip_amino = 1)

Description

Plot deuterium uptake curve for selected peptides

Usage

plot_uptake_curve(
  uc_dat,
  theoretical = FALSE,
  fractional = FALSE,
  uncertainty_type = "ribbon",
  log_x = TRUE,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

The function plot_uptake_curve generates the deuterium uptake curve for selected peptides from selected protein. On X-axis there are time points of measurements. On Y-axis there is deuterium uptake in selected form. The combined and propagated uncertainty can be presented as ribbons or error bars.

Value

a ggplot object.

See Also

read_hdx calculate_kinetics calculate_peptide_kinetics create_kinetic_dataset

Examples

uc_dat <- calculate_kinetics(alpha_dat, protein = "db_eEF1Ba",
                             sequence = "GFGDLKSPAGL", 
                             state = "Alpha_KSCN",
                             start = 1, end = 11,
                             time_0 = 0, time_100 = 1440)
plot_uptake_curve(uc_dat = uc_dat, 
                  theoretical = FALSE, 
                  fractional = TRUE)

Description

Volcano plot for differential deuterium uptake between two biological states

Usage

plot_volcano(
  p_dat,
  state_1 = "",
  state_2 = "",
  adjust_axes = TRUE,
  show_confidence_limits = FALSE,
  confidence_level = 0.98,
  color_times = TRUE,
  show_insignificant_grey = FALSE,
  hide_insignificant = FALSE,
  fractional = FALSE,
  theoretical = FALSE,
  interactive = getOption("hadex_use_interactive_plots")
)

Arguments

Details

The function plot_volcano generates the volcano plot based on supplied p_dat. On X-axis there is differential deuterium uptake in selected form. On Y-axis there is the P-value from t-Student test between two biological states. Based on selected confidence level, the confidence limits are calculated to indicate statistically significant values - shown as red dotted lines. The values that are in upper left and right corners pass the hybrid test.

Value

a ggplot object.

References

Hageman, T. S. & Weis, D. D. Reliable Identification of Significant Differences in Differential Hydrogen Exchange-Mass Spectrometry Measurements Using a Hybrid Significance Testing Approach. Anal Chem 91, 8008–8016 (2019).

Houde, D., Berkowitz, S.A., and Engen, J.R. (2011). The Utility of Hydrogen/Deuterium Exchange Mass Spectrometry in Biopharmaceutical Comparability Studies. J Pharm Sci 100, 2071–2086.

See Also

create_p_diff_uptake_dataset

Examples

p_dat <- create_p_diff_uptake_dataset(alpha_dat)
plot_volcano(p_dat, show_confidence_limits = TRUE)

plot_volcano(p_dat, show_confidence_limits = TRUE, show_insignificant_grey = TRUE)
plot_volcano(p_dat, show_confidence_limits = TRUE, hide_insignificant = TRUE)

Description

This function produces the data in format suitable for HDX-Viewer. If necessary, this result can be downloaded as the csv file with download indicator set to true.

Usage

prepare_hdxviewer_export(
  x_dat,
  differential = FALSE,
  fractional = TRUE,
  theoretical = FALSE,
  download = FALSE,
  file_path = tempdir()
)

Arguments

Value

a data.frame object

Examples

# disabled due to long execution time 

kin_dat <- create_uptake_dataset(alpha_dat, states = "Alpha_KSCN" )
aggregated_dat <- create_aggregated_uptake_dataset(kin_dat)
diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
diff_aggregated_dat <- create_aggregated_diff_uptake_dataset(diff_uptake_dat)
prepare_hdxviewer_export(aggregated_dat, differential = FALSE)
# prepare_hdxviewer_export(aggregated_dat, differential = TRUE) # shouldnt work
prepare_hdxviewer_export(diff_aggregated_dat, differential = TRUE)
# prepare_hdxviewer_export(aggregated_dat, differential = FALSE, download = TRUE) # writes a file

Description

Import HDX-MS datafile and validate its content

Usage

read_hdx(filename, separator = ",")

Arguments

Details

The function read_hdx generates a dataset read from the supplied datafile. The files produced by DynamX 3.0 or 2.0 in 'cluster data' format and 'tables' file from HDeXaminer are handled. Moreover, the data should include at least two replicates of the experiment to calculate the uncertainty of the measurement. For the files of HDeXaminer origin, the rows with no complete information (e.q. missing 'Exp Cent' value) are removed. The 'Confidence' column is preserved as the user should have impact on accepting rows based on their Confidence flag. Moreover, those files need action from the user - to confirm data processing (e.q. FD time point), choose accepted confidence values and make some change of the labels using update_hdexaminer_file function. For further information check the documentation. IMPORTANT! The files of HDeXaminer origin MUST be processed by hand or by update_hdexaminer_file function to fit the input of processing functions e.q. calculate_state_uptake or calculate_diff_uptake.

Value

a data.frame object

See Also

update_hdexaminer_file create_control_dataset calculate_state_uptake

Examples

dat <- read_hdx(system.file(package = "HaDeX2", 
                     "HaDeX/data/alpha.csv"))
head(dat)

Description

Reconstruct protein sequence from experimental data

Usage

reconstruct_sequence(
  dat,
  protein = dat[["Protein"]][1],
  states = unique(dat[["State"]]),
  end = NULL
)

Arguments

Details

The function reconstruct_sequence generates protein sequence from supplied experimental data. For a position not covered, letter x is shown. If the C-terminus of protein is not covered, there is a possibility to manually fix the protein length by passing a value to the 'end' parameter.

Value

a character object.

See Also

read_hdx

Examples

reconstruct_sequence(alpha_dat)

Description

Function plots the aggregated uptake data with regard to submitted parameters in a friendly form. Designed for GUI.

Usage

show_aggregated_uptake_data(
  aggregated_dat,
  differential = FALSE,
  fractional = TRUE,
  theoretical = FALSE
)

Arguments

Value

a data.frame object

Examples

# disabled due to long execution time 

kin_dat <- create_uptake_dataset(alpha_dat, states = "Alpha_KSCN")
aggregated_dat <- create_aggregated_uptake_dataset(kin_dat)
show_aggregated_uptake_data(aggregated_dat)

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
aggregated_diff_dat <- create_aggregated_diff_uptake_dataset(diff_uptake_dat)
show_aggregated_uptake_data(aggregated_diff_dat, differential = TRUE)

Description

This function prepares the data used in coverage heatmap to be shown in user-friendly way.

Usage

show_coverage_heatmap_data(x_dat, value = NULL)

Arguments

Value

a data.table object

Examples

# auc data
auc_dat <- calculate_auc(create_uptake_dataset(alpha_dat))
show_coverage_heatmap_data(auc_dat, value = "auc")

# back-exchange
bex_dat <- calculate_back_exchange(alpha_dat)
show_coverage_heatmap_data(bex_dat, value = "back_exchange")

Description

Present differential deuterium uptake values in selected form

Usage

show_diff_uptake_data(
  diff_uptake_dat,
  theoretical = FALSE,
  fractional = FALSE,
  renamed = TRUE
)

Arguments

Details

The function show_uptake_data generates a subsets of the diff_uptake_dat based on selected parameters. The numerical values are rounded to 4 places. The names of columns are changed to user-friendly ones.

Value

a data.frame object

See Also

read_hdx create_diff_uptake_dataset

Examples

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
head(show_diff_uptake_data(diff_uptake_dat))

Description

Present differential deuterium uptake values in selected form, accompanied by the significance

Usage

show_diff_uptake_data_confidence(
  diff_uptake_dat,
  theoretical = FALSE,
  fractional = FALSE,
  confidence_level = 0.98,
  hybrid = FALSE
)

Arguments

Details

The function show_uptake_data generates a subsets of the uptake dat based on selected parameters. It contains the information if the value is statistically significant at selected confidence level. The numerical values are rounded to 4 places. The names of columns are changed to user-friendly ones.

Value

a data.frame object

See Also

create_diff_uptake_dataset plot_differential

Examples

diff_uptake_dat <- create_diff_uptake_dataset(alpha_dat)
show_diff_uptake_data_confidence(diff_uptake_dat)

Description

Presents peptide overlap on protein sequence data, based on the supplied parameters.

Usage

show_overlap_data(
  dat,
  protein = dat[["Protein"]][1],
  state = dat[["State"]][1],
  start = min(dat[["Start"]]),
  end = max(dat[["End"]])
)

Arguments

Details

The data frame presents all the peptides in given state, with its start and end position on the protein sequence. This data is available in the GUI.

Value

a data.frame object.

See Also

read_hdx plot_overlap

Examples

show_overlap_data(alpha_dat)

Description

Present differential deuterium uptake values in selected form

Usage

show_p_diff_uptake_data(
  p_diff_uptake_dat,
  theoretical = FALSE,
  fractional = FALSE,
  renamed = TRUE
)

Arguments

Details

The function show_uptake_data generates a subsets of the diff_uptake_dat based on selected parameters. The numerical values are rounded to 4 places. The names of columns are changed to user-friendly ones.

Value

a data.frame object

See Also

read_hdx create_diff_uptake_dataset

Examples

p_diff_uptake_dat <- create_p_diff_uptake_dataset(alpha_dat)
head(show_p_diff_uptake_data(p_diff_uptake_dat))

Description

Show the charge measurements from replicates for peptide in specific time point.

Usage

show_peptide_charge_measurement(
  dat,
  protein = dat[["Protein"]][1],
  state = dat[["State"]][1],
  sequence = dat[["Sequence"]][1],
  time_t = unique(dat[["Exposure"]])[3]
)

Arguments

Details

This function shows the measurements of charge from different replicates for specific peptide in specific state in specific time point of measurement.

Value

a data.frame object.

See Also

read_hdx plot_peptide_charge_measurement

Examples

show_peptide_charge_measurement(alpha_dat)

Description

Show the mass measurements from replicates for peptide in specific time point.

Usage

show_peptide_mass_measurement(
  rep_mass_dat,
  protein = rep_mass_dat[["Protein"]][1],
  state = rep_mass_dat[["State"]][1],
  sequence = rep_mass_dat[["Sequence"]][1],
  time_t = unique(rep_mass_dat[["Exposure"]])[3]
)

Arguments

Details

This function shows the measurements of mass from different replicates for specific peptide in specific state in specific time point of measurement.

Value

a data.frame object.

See Also

read_hdx calculate_exp_masses_per_replicate calculate_exp_masses calculate_state_uptake calculate_diff_uptake

Examples

rep_mass_dat <- calculate_exp_masses_per_replicate(alpha_dat)
show_peptide_mass_measurement(rep_mass_dat)

Description

Generates quality control data, based on the supplied parameters.

Usage

show_quality_control_data(qc_dat)

Arguments

Details

This data frame presents the mean uncertainty in function of selected maximal exchange control time of measurement. This data is available in the GUI.

Value

a data.frame object.

See Also

create_quality_control_dataset plot_quality_control

Examples

qc_dat <- create_quality_control_dataset(alpha_dat)  
show_quality_control_data(qc_dat)

Description

Show histogram data on number of replicates per peptide in one or multiple time point of measurement.

Usage

show_replicate_histogram_data(rep_dat)

Arguments

Details

The function shows the information about number of replicates for peptides in one or multiple time point of measurement, depends on supplied data.

Value

a data.frame object.

See Also

create_replicate_dataset plot_replicate_histogram

Examples

rep_dat <- create_replicate_dataset(alpha_dat)
show_replicate_histogram_data(rep_dat)

Description

Show summary table

Usage

show_summary_data(
  dat,
  confidence_level = "",
  protein_length = max(dat[["End"]])
)

Arguments

Details

The format in the table is suggested by the community and should be provided for experimental data.

Value

a data.table object

References

Masson, G.R., Burke, J.E., Ahn, N.G., Anand, G.S., Borchers, C., Brier, S., Bou-Assaf, G.M., Engen, J.R., Englander, S.W., Faber, J., et al. (2019). Recommendations for performing, interpreting and reporting hydrogen deuterium exchange mass spectrometry (HDX-MS) experiments. Nat Methods 16, 595–602

See Also

read_hdx

Examples

show_summary_data(alpha_dat)

Description

Present deuterium uptake curve data

Usage

show_uc_data(uc_dat, theoretical = FALSE, fractional = FALSE)

Arguments

Details

The function show_uptake_data generates a subsets of the uc_dat based on selected parameters. The numerical values are rounded to 4 places. The names of columns are changed to user-friendly ones.

Value

a data.frame object

See Also

read_hdx calculate_kinetics calculate_peptide_kinetics

Examples

uc_dat <- calculate_kinetics(alpha_dat,
                             sequence = "GFGDLKSPAGL", 
                             state = "ALPHA_Gamma",
                             start = 1, end = 11)
show_uc_data(uc_dat)

Description

Present deuterium uptake values in selected form

Usage

show_uptake_data(
  uptake_dat,
  theoretical = FALSE,
  fractional = FALSE,
  renamed = TRUE
)

Arguments

Details

The function show_uptake_data generates a subsets of the uptake_dat based on selected parameters. The numerical values are rounded to 4 places. The names of columns are changed to user-friendly ones.

Value

a data.frame object

See Also

read_hdx create_uptake_dataset

Examples

uptake_dat <- create_uptake_dataset(alpha_dat)
show_uptake_data(uptake_dat)

Description

Update data from HDeXaminer file

Usage

update_hdexaminer_file(
  dat,
  fd_time,
  old_protein_name = NULL,
  new_protein_name = NULL,
  old_state_name = NULL,
  new_state_name = NULL,
  confidence = c("High", "Medium")
)

Arguments

Details

The function update_hdexaminer_file changes the data read from HDeXaminer file. Data from HDeXaminer is condensed and automated data retrieving may be corrected by the user. The original file has a mark "FD" for fully deuterated data instead of numerical value for time point (provided in minutes) that is not consistent for workflow and not enough for precise data description. Moreover, the data about both protein and state is included in one column and for detailed information function update_hdexaminer_file allows to change them.

Value

a data.frame object

See Also

read_hdx calculate_kinetics plot_coverage plot_position_frequency reconstruct_sequence