Package 'cascade'

Title: Contextualizing untargeted Annotation with Semi-quantitative Charged Aerosol Detection for pertinent characterization of natural Extracts
Description: This package provides the infrastructure to perform Automated Composition Assessment of Natural Extracts.
Authors: Adriano Rutz
Maintainer: Adriano Rutz <[email protected]>
License: AGPL (>= 3)
Version: 0.0.0.9002
Built: 2026-10-14 14:04:06 UTC
Source: https://github.com/adafede/cascade

Help Index

Add chromato line

Description

Add chromato line

Usage

add_chromato_line(
  plot,
  chromato,
  shift = 0,
  normalize_time,
  name,
  color,
  polarity = "pos"
)

Arguments

plot

Plot
chromato

Chromato
shift

Shift
normalize_time

Normalize time
name

Name
color

Color
polarity

Polarity

Value

A plot with added chromato line

Examples

NULL

Baseline chromatogram

Description

Baseline chromatogram

Usage

baseline_chromatogram(df, method = "peakDetection", ...)

Arguments

df

Dataframe
method

Baseline correction method. Default is "peakDetection". See baseline for available methods including: "als", "fillPeaks", "irls", "lowpass", "medianWindow", "modpolyfit", "peakDetection", "rfbaseline", "rollingBall", "shirley", "TAP".
...

Additional arguments passed to baseline.

Value

A dataframe with baselined chromatogram

Examples

NULL

CASCADE Example Datasets

Description

Example datasets included with CASCADE for demonstration and testing purposes. All data is stored as data.frame format for efficiency, and is converted to tidytable::tidytable when loaded via the load_* functions.

Usage

cascade_annotations

cascade_features

cascade_features_informed

cascade_features_not_informed

cascade_chromatograms_positive

cascade_chromatograms_negative

cascade_ms_data

Format

cascade_annotations: data.frame, 3471 rows × 58 columns cascade_features: data.frame, 3471 rows × 101 columns cascade_features_informed: data.frame, 3800 rows × 11 columns cascade_features_not_informed: data.frame, 910 rows × 11 columns cascade_chromatograms_positive: data.frame, 122541 rows × 3 columns cascade_chromatograms_negative: data.frame, 122079 rows × 3 columns cascade_ms_data: MSnbase::MSnExp object

An object of class data.frame with 3471 rows and 58 columns.

An object of class data.frame with 3471 rows and 101 columns.

An object of class data.frame with 3800 rows and 11 columns.

An object of class data.frame with 910 rows and 11 columns.

An object of class data.frame with 122541 rows and 3 columns.

An object of class data.frame with 122079 rows and 3 columns.

An object of class MSnExp with 1 rows and 1 columns.

cascade_annotations

Metabolite annotation table from a Swertia extract analyzed with TIMA. Contains 3471 unique features with their chemical and taxonomic contextualizations.

cascade_features

Complete mzMine feature table. Contains 3471 features with m/z, retention time, and intensity.

cascade_features_informed

CAD-detected peaks that matched annotation hypotheses. Contains 3800 peak-feature matches.

cascade_features_not_informed

CAD-detected peaks that did NOT match any annotation hypothesis. Contains 910 peak-feature matches.

cascade_chromatograms_positive

Chromatogram traces from positive-mode analysis. Tidy long-form data.frame with 3 columns.

cascade_chromatograms_negative

Chromatogram traces from negative-mode analysis. Tidy long-form data.frame with 3 columns.

cascade_ms_data

Example MS data as an MSnbase::MSnExp object. Required for full MS workflow.

Change intensity name

Description

Change intensity name

Usage

change_intensity_name(df, name_rt = "rtime", name_intensity = "intensity")

Arguments

df

Dataframe
name_rt

Name RT
name_intensity

Name intensity

Value

A dataframe with changed intensity name

Examples

NULL

Check chromatograms

Description

Check chromatograms

Usage

check_chromatograms(
  chromatograms = c("bpi_pos", "cad_pos", "pda_pos"),
  chromatograms_list,
  normalize_time = FALSE,
  shift_cad = 0,
  shift_pda = 0,
  type = "improved"
)

Arguments

chromatograms

Chromatograms
chromatograms_list

Chromatograms list
normalize_time

Normalized time
shift_cad

Shift CAD
shift_pda

Shift PDA
type

Type

Value

A plot

Examples

NULL

Check chromatograms alignment

Description

Check chromatograms alignment

Usage

check_chromatograms_alignment(
  file_negative = NULL,
  file_positive = NULL,
  time_min = 0.5,
  time_max = 32.5,
  cad_shift = 0.05,
  pda_shift = 0.1,
  fourier_components = 0.01,
  frequency = 1,
  resample = 1,
  chromatograms = c("bpi_pos", "cad_pos", "pda_pos"),
  headers = c(bpi = "BasePeak_0", pda = "PDA#1_TotalAbsorbance_0", cad = "UV#1_CAD_1_0"),
  type = "baselined",
  normalize_intensity = TRUE,
  normalize_time = FALSE,
  show_example = FALSE,
  intensity_floor = 0.001,
  k2 = 250,
  k4 = 1250000,
  sigma = 0.05,
  smoothing_width = 8,
  baseline_method = "peakDetection",
  improve_signal = TRUE
)

Arguments

file_negative

Negative file path
file_positive

Positive file path
time_min

Minimum time in minutes. Default is 0.5.
time_max

Maximum time in minutes. Default is 32.5.
cad_shift

CAD time shift in minutes. Default is 0.05.
pda_shift

PDA time shift in minutes. Default is 0.1.
fourier_components

Fraction of Fourier components to keep. Default is 0.01.
frequency

Acquisition frequency in Hz. Default is 1.
resample

Resampling factor. Default is 1.
chromatograms

Chromatograms to plot. Default is c("bpi_pos", "cad_pos", "pda_pos").
headers

Named vector mapping detector types to header names in the mzML file.
type

Type of chromatogram to display. Either "baselined" or "improved". Default is "baselined".
normalize_intensity

Normalize intensity? Default is TRUE.
normalize_time

Normalize time? Default is FALSE.
show_example

Show example data? Default is FALSE.
intensity_floor

Small positive value for intensity floor. Default is 0.001.
k2

K2 parameter for signal sharpening. Default is 250.
k4

K4 parameter for signal sharpening. Default is 1250000.
sigma

Sigma parameter for signal sharpening. Default is 0.05.
smoothing_width

Smoothing width for signal sharpening. Default is 8.
baseline_method

Method for baseline correction. Default is "peakDetection".
improve_signal

Logical. Whether to apply signal improvement (Fourier filtering and sharpening). Default is TRUE.

Value

A plot with (non-)aligned chromatograms

Examples

## Not run: 
check_chromatograms_alignment(show_example = TRUE)

## End(Not run)

Check export dir

Description

Check export dir

Usage

check_export_dir(dir)

Arguments

dir

Dir

Value

A log of checked dir

Examples

NULL

Check chromatograms alignment

Description

Check chromatograms alignment

Usage

check_peaks_integration(
  file = NULL,
  features = NULL,
  detector = "cad",
  chromatogram = "baselined",
  headers = c(bpi = "BasePeak_0", pda = "PDA#1_TotalAbsorbance_0", cad = "UV#1_CAD_1_0"),
  min_area = 0.005,
  min_intensity = 10000,
  shift = 0.05,
  show_example = FALSE,
  fourier_components = 0.01,
  time_min = 0.5,
  time_max = 32.5,
  frequency = 1,
  resample = 1,
  intensity_floor = 0.001,
  k2 = 250,
  k4 = 1250000,
  sigma = 0.05,
  smoothing_width = 8,
  baseline_method = "peakDetection",
  sd_max = 50,
  max_iter = 1000,
  noise_threshold = 0.001,
  fit = "egh",
  intensity_threshold = 0.1,
  improve_signal = TRUE
)

Arguments

file

File path
features

Features path
detector

Detector type (e.g., "cad", "bpi", "pda")
chromatogram

Chromatogram type. One of "original", "improved", or "baselined". Default is "baselined".
headers

Named vector mapping detector types to header names.
min_area

Minimum area fraction for peak filtering. Default is 0.005.
min_intensity

Minimum intensity for feature filtering. Default is 1E4.
shift

Time shift in minutes. Default is 0.05.
show_example

Show example data? Default is FALSE.
fourier_components

Fraction of Fourier components to keep. Default is 0.01.
time_min

Time min in minutes. Default is 0.5.
time_max

Time max in minutes. Default is 32.5.
frequency

Acquisition frequency in Hz. Default is 1.
resample

Resampling factor. Default is 1.
intensity_floor

Small positive value for intensity floor. Default is 0.001.
k2

K2 parameter for signal sharpening. Default is 250.
k4

K4 parameter for signal sharpening. Default is 1250000.
sigma

Sigma parameter for signal sharpening. Default is 0.05.
smoothing_width

Smoothing width for signal sharpening. Default is 8.
baseline_method

Method for baseline correction. Default is "peakDetection".
sd_max

Maximum standard deviation for peak filtering. Default is 50.
max_iter

Maximum iterations for peak fitting. Default is 1000.
noise_threshold

Noise threshold for peak detection. Default is 0.001.
fit

Peak fitting method. One of "egh", "gaussian", or "raw". Default is "egh".
intensity_threshold

Minimum normalized intensity threshold for filtering. Default is 0.1.
improve_signal

Logical. Whether to apply signal improvement. Default is TRUE.

Value

A plot with (non-)aligned chromatograms

Examples

## Not run: 
check_peaks_integration(show_example = TRUE)

## End(Not run)

Compare peaks

Description

Compare peaks

Usage

compare_peaks(x, list_ms_peaks, peaks_prelist)

Arguments

x

X
list_ms_peaks

list_ms_peaks
peaks_prelist

peaks_prelist

Value

A comparison score

Examples

NULL

Deriv

Description

Deriv

Usage

deriv(x, y)

Arguments

x

X
y

Y

Value

The derivative

Examples

NULL

Extract chromatogram

Description

Extract chromatogram

Usage

extract_chromatogram(list, type, headers)

Arguments

list

List
type

Type
headers

Headers

Value

An extracted chromatogram

Examples

NULL

Extract MS peak

Description

Extract MS peak

Usage

extract_ms_peak(x)

Arguments

x

X

Value

A peak

Examples

NULL

Extract MS progress

Description

Extract MS progress

Usage

extract_ms_progress(xs, ms_data, rts, mzs, nrows)

Arguments

xs

XS
ms_data

MS Data
rts

RTs
mzs

MZs
nrows

N rows

Value

A list of extracted MS peaks

Examples

NULL

Filter FFT

Description

Filter FFT

Usage

filter_fft(x, components)

Arguments

x

X
components

Components

Value

The fourier filtered x

Examples

NULL

Generate IDs

Description

Generate IDs

Usage

generate_ids(
  taxa = c("Swertia", "Kopsia", "Ginkgo"),
  comparison = NULL,
  no_stereo = TRUE,
  filter_ms_conditions = TRUE,
  start = "0",
  end = "9999",
  limit = "1000000"
)

Arguments

taxa

Taxa
comparison

Comparison
no_stereo

No stereo
filter_ms_conditions

Filter MS conditions
start

Start
end

End
limit

Limit

Value

IDs

Examples

## Not run: 
generate_ids()

## End(Not run)

Generate pseudochromatograms

Description

Generate pseudochromatograms

Usage

generate_pseudochromatograms(
  annotations = NULL,
  features_informed = NULL,
  features_not_informed = NULL,
  file = NULL,
  headers = c(bpi = "BasePeak_0", pda = "PDA#1_TotalAbsorbance_0", cad = "UV#1_CAD_1_0"),
  detector = "cad",
  show_example = FALSE,
  min_confidence = 0.4,
  min_similarity_prefilter = 0.6,
  min_similarity_filter = 0.8,
  mode = "pos",
  organism = "Swertia chirayita",
  fourier_components = 0.01,
  frequency = 1,
  resample = 1,
  shift = 0.05,
  time_min = 0.5,
  time_max = 32.5,
  intensity_floor = 0.001,
  k2 = 250,
  k4 = 1250000,
  sigma = 0.05,
  smoothing_width = 8,
  baseline_method = "peakDetection",
  improve_signal = TRUE
)

Arguments

annotations

Annotations file path
features_informed

Features informed file path
features_not_informed

Features not informed file path
file

mzML file path
headers

Named vector mapping detector types to header names.
detector

Detector type (e.g., "cad", "bpi", "pda")
show_example

Show example data? Default is FALSE.
min_confidence

Minimum confidence score. Default is 0.4.
min_similarity_prefilter

Minimum similarity for pre-filtering. Default is 0.6.
min_similarity_filter

Minimum similarity for final filtering. Default is 0.8.
mode

Ionization mode. Either "pos" or "neg". Default is "pos".
organism

Organism name for taxonomic filtering.
fourier_components

Fraction of Fourier components to keep. Default is 0.01.
frequency

Acquisition frequency in Hz. Default is 1.
resample

Resampling factor. Default is 1.
shift

Time shift in minutes. Default is 0.05.
time_min

Time min in minutes. Default is 0.5.
time_max

Time max in minutes. Default is 32.5.
intensity_floor

Small positive value for intensity floor. Default is 0.001.
k2

K2 parameter for signal sharpening. Default is 250.
k4

K4 parameter for signal sharpening. Default is 1250000.
sigma

Sigma parameter for signal sharpening. Default is 0.05.
smoothing_width

Smoothing width for signal sharpening. Default is 8.
baseline_method

Method for baseline correction. Default is "peakDetection".
improve_signal

Logical. Whether to apply signal improvement. Default is TRUE.

Value

A list of plots

Examples

## Not run: 
generate_pseudochromatograms(show_example = TRUE)

## End(Not run)

Generate IDs

Description

Generate IDs

Usage

generate_tables(
  annotations = NULL,
  file_negative = NULL,
  file_positive = NULL,
  min_confidence = 0.4,
  show_example = FALSE,
  export_csv = TRUE,
  export_html = TRUE,
  export_dir = "data/processed",
  export_name = "cascade_table"
)

Arguments

annotations

Annotations
file_negative

File negative
file_positive

File positive
min_confidence

Min confidence
show_example

Show example? Default to FALSE
export_csv

Export CSV
export_html

Export HTML
export_dir

Export Dir
export_name

Export name

Value

Tables

Examples

## Not run: 
generate_tables()

## End(Not run)

Get peaks

Description

Get peaks

Usage

get_peaks(
  chrom_list,
  lambdas,
  fit = c("egh", "gaussian", "raw"),
  sd.max = 50,
  max.iter = 100,
  time.units = c("min", "s", "ms"),
  estimate_purity = FALSE,
  noise_threshold = 0.001,
  collapse = FALSE,
  ...
)

Arguments

chrom_list

Chrom list
lambdas

Lambdas
fit

Fit
sd.max

Sd max
max.iter

Max iter
time.units

Time units
estimate_purity

Estimate purity
noise_threshold

Noise Threshold
collapse

Collapse
...

...

Value

Peaks

Note

This was imported from {chromatographR} package and parallelization was removed as it was causing issues on Windows.

Author(s)

Ethan Bass

Source

https://github.com/ethanbass/chromatographR

Examples

NULL

Hierarchies grouped progress

Description

Hierarchies grouped progress

Usage

hierarchies_grouped_progress(xs)

Arguments

xs

XS

Value

A list of grouped hierarchies

Examples

NULL

Hierarchies Progress

Description

Hierarchies Progress

Usage

hierarchies_progress(xs, comparison)

Arguments

xs

XS
comparison

Comparison

Value

A list of hierarchies

Examples

NULL

Improve signal

Description

Improve signal

Usage

improve_signal(
  df,
  fourier_components = 0.01,
  frequency = 2,
  resample = 1,
  time_min = 0,
  time_max = Inf,
  intensity_floor = 0.001,
  k2 = 250,
  k4 = 1250000,
  sigma = 0.05,
  smoothing_width = 8
)

Arguments

df

Dataframe with columns 'rtime' and 'intensity'
fourier_components

Fraction of Fourier components to keep for filtering. Default is 0.01 (1%). Lower values provide more smoothing.
frequency

Acquisition frequency in Hz. Default is 2.
resample

Resampling factor. Default is 1.
time_min

Time min in minutes. Default is 0.
time_max

Time max in minutes. Default is Inf.
intensity_floor

Small positive value to ensure all intensities are strictly positive after shifting. Default is 0.001.
k2

K2 parameter for signal sharpening. Default is 250.
k4

K4 parameter for signal sharpening. Default is 1250000.
sigma

Sigma parameter for signal sharpening. Default is 0.05.
smoothing_width

Smoothing width for signal sharpening. Default is 8.

Value

A dataframe with improved signal

Examples

NULL

Improve signals progress

Description

Improve signals progress

Usage

improve_signals_progress(
  xs,
  fourier_components = 0.01,
  frequency = 2,
  resample = 1,
  time_min = 0,
  time_max = Inf,
  intensity_floor = 0.001,
  k2 = 250,
  k4 = 1250000,
  sigma = 0.05,
  smoothing_width = 8
)

Arguments

xs

List of dataframes with 'rtime' and 'intensity' columns
fourier_components

Fraction of Fourier components to keep. Default is 0.01.
frequency

Acquisition frequency in Hz. Default is 2.
resample

Resampling factor. Default is 1.
time_min

Time min in minutes. Default is 0.
time_max

Time max in minutes. Default is Inf.
intensity_floor

Small positive value for intensity floor. Default is 0.001.
k2

K2 parameter for signal sharpening. Default is 250.
k4

K4 parameter for signal sharpening. Default is 1250000.
sigma

Sigma parameter for signal sharpening. Default is 0.05.
smoothing_width

Smoothing width for signal sharpening. Default is 8.

Value

A list of data frames with improved signals

Examples

NULL

Join peaks

Description

Join peaks

Usage

join_peaks(chromatograms, peaks, min_area)

Arguments

chromatograms

Chromatograms
peaks

Peaks
min_area

Min area

Value

A dataframe with joined peaks

Examples

NULL

Keep best candidates

Description

Keep best candidates

Usage

keep_best_candidates(df)

Arguments

df

Dataframe

Value

A dataframe containing the best candidates only

Examples

NULL

Load annotations

Description

Load annotations

Usage

load_annotations(file = NULL, show_example = FALSE, mode = "pos")

Arguments

file

File
show_example

Show example? Default to FALSE
mode

Mode

Value

A table of annotations

Examples

NULL

Load chromatograms

Description

Load chromatograms

Usage

load_chromatograms(
  file = NULL,
  headers = c(bpi = "BasePeak_0", pda = "PDA#1_TotalAbsorbance_0", cad = "UV#1_CAD_1_0"),
  show_example = FALSE,
  example_polarity = "pos"
)

Arguments

file

File
headers

Headers
show_example

Show example? Default to FALSE
example_polarity

Example polarity

Value

A list of chromatograms

Examples

NULL

Load features

Description

Load features

Usage

load_features(file = NULL, show_example = FALSE)

Arguments

file

File
show_example

Show example? Default to FALSE

Value

A table of features

Examples

NULL

Load features informed

Description

Load features informed

Usage

load_features_informed(file = NULL, show_example = FALSE)

Arguments

file

File
show_example

Show example? Default to FALSE

Value

A table of informed features

Examples

NULL

Load features not informed

Description

Load features not informed

Usage

load_features_not_informed(file = NULL, show_example = FALSE)

Arguments

file

File
show_example

Show example? Default to FALSE

Value

A table of non informed features

Examples

NULL

Load MS data

Description

Load MS data

Usage

load_ms_data(file = NULL, show_example = FALSE)

Arguments

file

File
show_example

Show example? Default to FALSE

Value

MS data

Examples

NULL

Load name

Description

Load name

Usage

load_name(
  file = NULL,
  default = "210619_AR_06_V_03_2_01.mzML",
  show_example = FALSE
)

Arguments

file

File
default

Default
show_example

Show example? Default to FALSE

Value

A name

Examples

NULL

Make chromatographiable

Description

Make chromatographiable

Usage

make_chromatographiable(
  df,
  mass_min = 50,
  mass_max = 1500,
  logp_min = -1,
  logp_max = 6
)

Arguments

df

Dataframe
mass_min

Mass min
mass_max

Mass max
logp_min

Log P min
logp_max

Log P max

Value

A dataframe containing chromatographiable compounds

Examples

NULL

Make confident

Description

Make confident

Usage

make_confident(df, score)

Arguments

df

Dataframe
score

Score

Value

A dataframe containing annotations with scores above the confidence threshold set

Examples

NULL

Make no stereo

Description

Make no stereo

Usage

make_no_stereo(df)

Arguments

df

Dataframe

Value

A dataframe with no stereo structures

Examples

NULL

Make other

Description

Make other

Usage

make_other(dataframe, value = "peak_area")

Arguments

dataframe

Dataframe
value

Value

Value

A dataframe with harmonized "other" subcategories

Examples

NULL

Middle pts

Description

Middle pts

Usage

middle_pts(x)

Arguments

x

X

Value

Middle pts

Examples

NULL

Molinfo

Description

Molinfo

Usage

molinfo(x)

Arguments

x

X

Value

A mol image

Examples

NULL

No other

Description

No other

Usage

no_other(dataframe)

Arguments

dataframe

Dataframe

Value

A dataframe with no other

Examples

NULL

Normalize chromato

Description

Normalize chromato

Usage

normalize_chromato(x, df_xy, intensity_threshold = 0.1)

Arguments

x

X
df_xy

Df X Y
intensity_threshold

Minimum normalized intensity threshold for filtering. Default is 0.1. Set to 0 to keep all points.

Value

A normalized chromato

Examples

NULL

Normalize chromatograms list

Description

Normalize chromatograms list

Usage

normalize_chromatograms_list(
  list,
  shift = 0,
  normalize_intensity = TRUE,
  normalize_time = FALSE
)

Arguments

list

List
shift

Shift
normalize_intensity

Normalize time
normalize_time

Normalize intensity

Value

A dataframe with normalized chromatograms

Examples

NULL

P ACN I

Description

P ACN I

Usage

p_acn_i(acn_eluent, q1, q2, q3)

Arguments

acn_eluent

ACN eluent
q1

Q1
q2

Q2
q3

Q3

Value

P ACN I

Examples

NULL

Peaks progress

Description

Peaks progress

Usage

peaks_progress(
  df_xy,
  sd_max = 50,
  max_iter = 1000,
  noise_threshold = 0.001,
  fit = "egh"
)

Arguments

df_xy

Df X Y
sd_max

Maximum standard deviation for peak filtering. Default is 50.
max_iter

Maximum iterations for peak fitting. Default is 1000.
noise_threshold

Noise threshold for peak detection. Default is 0.001.
fit

Peak fitting method. One of "egh", "gaussian", or "raw". Default is "egh".

Value

A list of peaks

Examples

NULL

Plot histograms

Description

Plot histograms

Usage

plot_histograms(dataframe, chromatogram, label, y = "values", xlab = TRUE)

Arguments

dataframe

Dataframe
chromatogram

Chromatogram
label

Label
y

Y
xlab

Xlab

Value

A plot of histograms

Examples

NULL

Plot histograms confident

Description

Plot histograms confident

Usage

plot_histograms_confident(
  dataframe,
  chromatogram,
  level = "max",
  time_min,
  time_max
)

Arguments

dataframe

Dataframe
chromatogram

Chromatogram
level

Level
time_min

Time min
time_max

Time max

Value

A plot of confident histograms

Examples

NULL

Plot histograms litt

Description

Plot histograms litt

Usage

plot_histograms_litt(dataframe, label, y = "values", xlab = TRUE)

Arguments

dataframe

Dataframe
label

Label
y

Y
xlab

Xlab

Value

A plot of literature histograms

Examples

NULL

Plot histograms taxo

Description

Plot histograms taxo

Usage

plot_histograms_taxo(
  dataframe,
  chromatogram,
  level = "max",
  mode = "pos",
  time_min,
  time_max
)

Arguments

dataframe

Dataframe
chromatogram

Chromatogram
level

Level
mode

Mode
time_min

Time min
time_max

Time max

Value

A plot of taxo histograms

Examples

NULL

Plot peak detection

Description

Plot peak detection

Usage

plot_peak_detection(df1, df2, fun)

Arguments

df1

DF 1 containing chromatogram
df2

DF 2 containing peaks
fun

Fun

Value

A plot with (non-)detected peaks

Examples

NULL

Plot results 1

Description

Plot results 1

Usage

plot_results_1(list, chromatogram, mode = "pos", time_min, time_max)

Arguments

list

List
chromatogram

Chromatogram
mode

Mode
time_min

Time min
time_max

Time max

Value

A list of plots

Examples

NULL

Plot TIMA

Description

Plot TIMA

Usage

plot_tima(tables)

Arguments

tables

Tables

Value

Pretty plots

Examples

NULL

Prepare comparison

Description

Prepare comparison

Usage

prepare_comparison(
  features_informed = NULL,
  features_not_informed = NULL,
  candidates_confident,
  min_similarity_prefilter = 0.6,
  min_similarity_filter = 0.8,
  mode = "pos",
  show_example = FALSE,
  default_peak_area = 0.001
)

Arguments

features_informed

Features informed
features_not_informed

Features not informed
candidates_confident

Candidates confident
min_similarity_prefilter

Min similarity pre filter
min_similarity_filter

Min similarity filter
mode

Mode
show_example

Show example? Default to FALSE
default_peak_area

Default peak area for features without peak information. Default is 0.001.

Value

A list of peaks

Examples

NULL

Prepare features

Description

Prepare features

Usage

prepare_features(df, min_intensity, name)

Arguments

df

Df
min_intensity

Min intensity
name

Name

Value

A dataframe of prepared features

Examples

NULL

Prepare hierarchy

Description

Prepare hierarchy

Usage

prepare_hierarchy(
  dataframe,
  type = "analysis",
  detector = "ms",
  rescale = FALSE
)

Arguments

dataframe

Dataframe
type

Type
detector

Detector
rescale

Rescale

Value

A dataframe with prepared hierarchy

Examples

NULL

Prepare mz

Description

Prepare mz

Usage

prepare_mz(x)

Arguments

x

X

Value

A list of prepared mz's

Examples

NULL

Prepare peaks

Description

Prepare peaks

Usage

prepare_peaks(x)

Arguments

x

X

Value

Prepared peaks

Examples

NULL

Prepare plot

Description

Prepare plot

Usage

prepare_plot(dataframe, organism = "species")

Arguments

dataframe

Dataframe
organism

Organism

Value

A dataframe prepared for plots

Examples

NULL

Prepare plot 2

Description

Prepare plot 2

Usage

prepare_plot_2(dataframe)

Arguments

dataframe

Dataframe

Value

A dataframe prepared for plots

Examples

NULL

Prepare rt

Description

Prepare rt

Usage

prepare_rt(x, shift = 0)

Arguments

x

X
shift

Shift

Value

Prepared RTs

Examples

NULL

Prepare TIMA annotations

Description

Prepare TIMA annotations

Usage

prepare_tima_annotations(
  annotations = NULL,
  predicted_classes = FALSE,
  min_score_initial = 0,
  min_score_biological = 0,
  min_score_chemical = 0,
  min_score_final = 0,
  min_matched_peaks_absolute = 0L,
  min_matched_peaks_percentage = 0,
  min_peaks = 3L,
  libraries = c("gnps", "massbank", "merlin", "ISDB", "ISDB - Wikidata", "TIMA MS1"),
  show_example = FALSE
)

Arguments

annotations

annotations
predicted_classes

Show predicted classes? Default to FALSE
min_score_initial

Minimal initial score
min_score_biological

Minimal biological score
min_score_chemical

Minimal chemical score
min_score_final

Minimal final score
min_matched_peaks_absolute

Minimal number of matched peaks
min_matched_peaks_percentage

Minimal percentage of matched peaks
min_peaks

Minimal number of peaks in spectrum
libraries

Libraries to consider
show_example

Show example? Default to FALSE

Value

Prepared tables

Examples

NULL

Preprocess chromatograms

Description

Preprocess chromatograms

Usage

preprocess_chromatograms(
  detector = "cad",
  fourier_components = 0.01,
  frequency = 2,
  list,
  name,
  resample = 1,
  shift = 0,
  time_min = 0,
  time_max = Inf,
  intensity_floor = 0.001,
  k2 = 250,
  k4 = 1250000,
  sigma = 0.05,
  smoothing_width = 8,
  baseline_method = "peakDetection",
  improve_signal = TRUE
)

Arguments

detector

Detector type (e.g., "cad", "bpi", "pda")
fourier_components

Fraction of Fourier components to keep. Default is 0.01.
frequency

Acquisition frequency in Hz. Default is 2.
list

List of chromatograms
name

Sample name(s)
resample

Resampling factor. Default is 1.
shift

Time shift in minutes. Default is 0.
time_min

Time min in minutes. Default is 0.
time_max

Time max in minutes. Default is Inf.
intensity_floor

Small positive value for intensity floor. Default is 0.001.
k2

K2 parameter for signal sharpening. Default is 250.
k4

K4 parameter for signal sharpening. Default is 1250000.
sigma

Sigma parameter for signal sharpening. Default is 0.05.
smoothing_width

Smoothing width for signal sharpening. Default is 8.
baseline_method

Method for baseline correction. Default is "peakDetection". See baseline for available methods.
improve_signal

Logical. Whether to apply signal improvement (Fourier filtering and sharpening). Default is TRUE. Set to FALSE to skip signal improvement and use original chromatograms.

Value

A list of preprocessed chromatograms

Examples

NULL

Preprocess peaks

Description

Preprocess peaks

Usage

preprocess_peaks(
  detector = "cad",
  df_features,
  df_long,
  df_xy,
  name,
  shift = 0,
  min_area = 0,
  sd_max = 50,
  max_iter = 1000,
  noise_threshold = 0.001,
  fit = "egh",
  intensity_threshold = 0.1
)

Arguments

detector

Detector
df_features

DF features
df_long

DF long
df_xy

DF X Y
name

Name
shift

shift
min_area

Minimum area
sd_max

Maximum standard deviation for peak filtering. Default is 50.
max_iter

Maximum iterations for peak fitting. Default is 1000.
noise_threshold

Noise threshold for peak detection. Default is 0.001.
fit

Peak fitting method. One of "egh", "gaussian", or "raw". Default is "egh".
intensity_threshold

Minimum normalized intensity threshold for filtering in normalize_chromato. Default is 0.1.

Value

A list of lists and dataframe with preprocessed peaks

Examples

NULL

Process compare peaks

Description

Process compare peaks

Usage

process_compare_peaks(
  file = NULL,
  features = NULL,
  type = "baselined",
  detector = "cad",
  headers = c(bpi = "BasePeak_0", pda = "PDA#1_TotalAbsorbance_0", cad = "UV#1_CAD_1_0"),
  export_dir = "data/interim/peaks",
  show_example = FALSE,
  fourier_components = 0.01,
  frequency = 1,
  min_area = 0.005,
  min_intensity = 10000,
  resample = 1,
  shift = 0.05,
  time_min = 0.5,
  time_max = 32.5
)

Arguments

file

File path
features

Features path
type

Type. "original", "baselined" or "improved"
detector

Detector
headers

Headers
export_dir

Export directory
show_example

Show example? Default to FALSE
fourier_components

Fourier components
frequency

Frequency
min_area

Min area
min_intensity

Min intensity
resample

Resample
shift

Shift
time_min

Time min
time_max

Time max

Value

A plot with (non-)aligned chromatograms

Examples

NULL

Queries progress

Description

Generates SPARQL queries for multiple taxa by fetching a query template from a remote repository and parameterizing it with taxon QIDs and filters.

Usage

queries_progress(
  xs,
  start = "0",
  end = "9999",
  limit = "1000000",
  query_url = NULL,
  query_part_1 = NULL,
  query_part_2 = NULL,
  query_part_3 = NULL,
  query_part_4 = NULL
)

Arguments

xs

Named list of taxon QIDs
start

Start year for publication date filter (character)
end

End year for publication date filter (character)
limit

Maximum number of results per query (character)
query_url

URL to the remote SPARQL query template. If NULL, uses default.
query_part_1

Deprecated. Kept for backward compatibility.
query_part_2

Deprecated. Kept for backward compatibility.
query_part_3

Deprecated. Kept for backward compatibility.
query_part_4

Deprecated. Kept for backward compatibility.

Value

A named list of parameterized SPARQL queries

Examples

## Not run: 
qids <- list(Swertia = "Q1234", Kopsia = "Q5678")
queries <- queries_progress(xs = qids, start = "2000", end = "2024")

## End(Not run)

Query a SPARQL endpoint efficiently

Description

Performs a SPARQL query and returns a data.table. Optimised for very large result sets (millions of rows):

  • Requests CSV (no IRI angle-bracket decoration, smallest text format)

  • Requests gzip transfer encoding (3-5x less data over the wire)

  • Streams the response directly to disk via curl (zero R memory use during download)

  • Parses with data.table::fread (C-level, multi-threaded)

Falls back to JSON for endpoints that do not support CSV.

Usage

query_wikidata(
  sparql_query,
  remove_url = TRUE,
  endpoint = "https://query.wikidata.org/sparql",
  agent = "https://github.com/bearloga/WikidataQueryServiceR",
  timeout = 3600L,
  fallback = TRUE,
  headers = NULL,
  post = FALSE
)

Arguments

sparql_query

Character. SPARQL query string.
remove_url

Logical. Strip ⁠http://www.wikidata.org/entity/⁠ prefix from character columns (default TRUE).
endpoint

Character. SPARQL endpoint URL.
agent

Character. User-Agent header string.
timeout

Integer. Total request timeout in seconds (default 3600).
fallback

Logical. Retry with QLever Wikidata endpoint on failure.
headers

Character or NULL. Optional Accept header used for backward compatibility with older versions. If set, this value is used as preferred response format.
post

Logical. If TRUE, send the SPARQL query as an HTTP POST request body (application/x-www-form-urlencoded) rather than as a GET query parameter. Required for endpoints such as QLever that do not accept GET requests.

Value

A data.table.

Examples

NULL

Second der

Description

Second der

Usage

second_der(x, y)

Arguments

x

X
y

Y

Value

The second derivative

Examples

NULL

Signal sharpening

Description

Signal sharpening

Usage

signal_sharpening(
  time,
  intensity,
  k2 = 250,
  k4 = 1250000,
  sigma = 0.05,
  Smoothing_width = 8,
  Baseline_adjust = 0
)

Arguments

time

time
intensity

intensity
k2

K2 parameter controlling the weight of the second derivative in signal sharpening. Default is 250. Lower values increase the sharpening effect from the second derivative.
k4

K4 parameter controlling the weight of the fourth derivative in signal sharpening. Default is 1250000. Lower values increase the sharpening effect from the fourth derivative.
sigma

Sigma parameter for derivative weighting. Default is 0.05. Higher values increase the overall sharpening effect.
Smoothing_width

Smoothing width for the running mean filter. Default is 8. Higher values provide more smoothing but reduce resolution.
Baseline_adjust

Baseline adjustment value. Default is 0.

Value

A sharpened signal

Examples

NULL

Tables progress

Description

Tables progress

Usage

tables_progress(xs, structures_classified)

Arguments

xs

XS
structures_classified

structures classified

Value

A list of tables

Examples

NULL

Taxon name to QID

Description

Taxon name to QID

Usage

taxon_name_to_qid(taxon_name)

Arguments

taxon_name

Taxon name

Value

A QID

Examples

## Not run: 
taxon_name_to_qid(taxon_name = "Gentiana lutea")

## End(Not run)

Transform MS

Description

Transform MS

Usage

transform_ms(x, min_intensity = 0.1)

Arguments

x

X
min_intensity

Minimum normalized intensity threshold for filtering. Default is 0.1. Set to 0 to keep all points.

Value

A list with transformed MS

Examples

NULL

Treemaps progress no title

Description

Treemaps progress no title

Usage

treemaps_progress_no_title(xs, type = "treemap", hierarchies)

Arguments

xs

XS
type

Type
hierarchies

Hierarchies

Value

A list of treemaps with no title

Examples

NULL

Wiki progress

Description

Wiki progress

Usage

wiki_progress(xs)

Arguments

xs

XS

Value

A list of results of Wikidata queries

Examples

NULL

Y as NA

Description

Y as NA

Usage

y_as_na(x, y)

Arguments

x

x
y

y

Value

Y's replaced as NA's in X

Examples

NULL