Web Application Reference#

This page contains auto-generated docs for PyHDX’ web application.

The functionality in can be controlled by Controllers which can be found in the left sidebar. The control parameters of every controller per app is listed in the sections below.

Main Application#

class pyhdx.web.controllers.PeptideFileInputControl(parent, **params)[source]#

Peptide Input

This controller allows users to input .csv file (Currently only DynamX format) of ‘state’ peptide uptake data. Users can then choose how to correct for back-exchange and which ‘state’ and exposure times should be used for analysis.

Input mode (Selector, default=’Manual’, options=[‘Manual’, ‘Batch’])

Input files label (String, default=’Input files:’)

Input files (List, bounds=(0, None), default=[])

HDX input files. Currently only support DynamX format

Batch file label (String, default=’Batch file (yaml)’)

Batch file (Parameter)

Batch file input:

Back exchange correction method (Selector, default=’FD Sample’, options=[‘FD Sample’, ‘Flat percentage’])

Select method of back exchange correction

FD State (Selector, options=[])

State used to normalize uptake

FD Exposure (Selector, options=[])

Exposure used to normalize uptake

Back exchange percentage (Number, bounds=(0, 100), default=28.0)

Global percentage of back-exchange

Experiment State (Selector, options=[])

State for selected experiment

Experiment Exposures (ListSelector, default=[], options=[‘’])

Selected exposure time to use

Drop first (Integer, bounds=(0, None), default=1)

Select the number of N-terminal residues to ignore.

Deuterium percentage (Number, bounds=(0, 100), default=90.0)

Percentage of deuterium in the labelling buffer

Temperature (K) (Number, bounds=(0, 373.15), default=293.15)

Temperature of the D-labelling reaction

pH read (Number, default=7.5)

pH of the D-labelling reaction, as read from pH meter

N term (Integer, default=1)

Index of the n terminal residue in the protein. Can be set to negative values to accommodate for purification tags. Used in the determination of intrinsic rate of exchange

C term (Integer, bounds=(0, None), default=0)

Index of the c terminal residue in the protein. Used for generating pymol export scriptand determination of intrinsic rate of exchange for the C-terminal residue

Sequence (String, default=’’)

Optional FASTA protein sequence

Dataset name (String, default=’’)

Add measurement(s) (Action)

Parse selected peptides for further analysis and apply back-exchange correction

HDX Measurements (ListSelector, options=[])

Lists added HDX-MS measurements

Additional GUI elements on:

class pyhdx.web.controllers.InitialGuessControl(parent, **params)[source]#

Initial Guesses

This controller allows users to derive initial guesses for D-exchange rate from peptide uptake data.

Fitting model (Selector, default=’Half-life (λ)’, options=[‘Half-life (λ)’, ‘Association’])

Choose method for determining initial guesses.

Dataset (for bounds) (Selector, default=’’, options=[])

Dataset to apply bounds to

Global bounds (Boolean, bounds=(0, 1), default=False)

Set bounds globally across all datasets

Lower bound (Number, default=0.0)

Lower bound for association model fitting

Upper bound (Number, default=0.0)

Upper bound for association model fitting

Guess name (String, default=’Guess_1’)

Name for the initial guesses

Calculate Guesses (Action)

Start initial guess fitting

Additional GUI elements on:

class pyhdx.web.controllers.FitControl(parent, **params)[source]#

ΔG Fit

This controller allows users to execute PyTorch fitting of the global data set.

Currently, repeated fitting overrides the old result.

Initial guess (Selector, options=[])

Name of dataset to use for initial guesses.

Guess mode (Selector, default=’One-to-one’, options=[‘One-to-one’, ‘One-to-many’])

Use initial guesses for each protein state (one-to-one) or use one initialguess for all protein states (one-to-many)

Guess state (Selector, options=[])

Which protein state to use for initial guess when using one-to-many guesses

Fit mode (Selector, default=’Single’, options=[‘Batch’, ‘Single’])

Stop loss (Number, bounds=(0, None), default=5e-06)

Threshold loss difference below which to stop fitting.

Stop patience (Integer, bounds=(1, None), default=50)

Number of epochs where stop loss should be satisfied before stopping.

Learning rate (Number, bounds=(0, None), default=10000.0)

Learning rate parameter for optimization.

Momentum (Number, bounds=(0, None), default=0.5)

Stochastic Gradient Descent momentum

Nesterov (Boolean, bounds=(0, 1), default=True)

Use Nesterov type of momentum for SGD

Epochs (Integer, bounds=(1, None), default=200000)

Maximum number of epochs (iterations.

Regularizer 1 (peptide axis) (Number, bounds=(0, None), default=1)

Value of the regularizer along residue axis.

Regularizer 2 (sample axis) (Number, bounds=(0, None), default=1)

Value of the regularizer along sample axis.

R2 reference (Selector, options=[])

Select reference state to use in batch fitting

Fit name (String, default=’Gibbs_fit_1’)

Name for for the fit result

Do Fitting (Action)

Start global fitting

Additional GUI elements on:

class pyhdx.web.controllers.DifferentialControl(parent, **params)[source]#

Differential HDX

Reference state (Selector, options=[])

Which of the states to use as reference

Comparison name (String, default=’comparison_1’)

Name for the comparison table

Add comparison (Action)

Additional GUI elements on:

class pyhdx.web.controllers.ColorTransformControl(parent, **param)[source]#

Color Transform

This controller allows users classify ‘mapping’ datasets and assign them colors.

Coloring can be either in discrete categories or as a continuous custom color map.

Target Quantity (Selector, options=[])

Current color transform (String, default=’’)

Mode (Selector, default=’Colormap’, options=[‘Colormap’, ‘Continuous’, ‘Discrete’])

Choose color mode (interpolation between selected colors).

Number of colours (Integer, bounds=(1, 10), default=2)

Number of classification colors.

Library (Selector, default=’pyhdx_default’, options=[‘pyhdx_default’, ‘user_defined’, ‘matplotlib’, ‘colorcet’])

Colormap (Selector, options=[])

Otsu (Action)

Automatically perform thresholding based on Otsu’s method.

Linear (Action)

Automatically perform thresholding by creating equally spaced sections.

No coverage (Color, allow_named=True, default=’#8c8c8c’)

Color to use for regions of no coverage

Color transform name (String, default=’’)

Name for the color transform to add

Update color transform (Action)

Additional GUI elements on:

class pyhdx.web.controllers.ProteinControl(parent, **params)[source]#

Protein Control

Input mode (Selector, default=’RCSB PDB Download’, options=[‘RCSB PDB Download’, ‘PDB File’])

Method of protein structure input

File binary (Parameter)

Corresponds to file upload value

Pdb id (String, default=’’)

RCSB ID of protein to download

Load structure (Action)

Highlight mode (Selector, default=’Single’, options=[‘Single’, ‘Range’])

Highlight range (Range, default=(1, 2), length=2, step=1)

Highlight value (Integer, default=1)

Highlight (Action)

Clear highlight (Action)

Additional GUI elements on:

class pyhdx.web.controllers.GraphControl(parent, **params)[source]#

Graph Control

Additional GUI elements on:

class pyhdx.web.controllers.FileExportControl(parent, **param)[source]#

File Export

<outdated docstring> This controller allows users to export and download datasets.

All datasets can be exported as .txt tables. ‘Mappable’ datasets (with r_number column) can be exported as .pml pymol script, which colors protein structures based on their ‘color’ column.

Target dataset (Selector, options=[])

Name of the dataset to export

Export format (Selector, default=’csv’, options=[‘csv’, ‘pprint’])

Format of the exported tables.’csv’ is machine-readable, ‘pprint’ is human-readable format

Additional GUI elements on:

class pyhdx.web.controllers.FigureExportControl(parent, **param)[source]#

Figure Export

Figure (Selector, default=’scatter’, options=[‘scatter’, ‘linear_bars’, ‘rainbowclouds’])

Table (Selector, options=[])

which table data to use for figure

Selection (Selector, options=[])

for scatter / rainbowclouds, which fit to use

Groupby (Selector, options=[])

for linear bars, how to group the bars

Reference (Selector, options=[])

Figure format (Selector, default=’png’, options=[‘png’, ‘pdf’, ‘svg’, ‘eps’])

Number of columns (Integer, bounds=(1, 4), default=2)

Number of columns in subfigure

Aspect ratio (Number, default=3.0)

Subfigure aspect ratio

Figure width (mm) (Number, bounds=(50, None), default=160.0)

Width of the output figure

Additional GUI elements on:

class pyhdx.web.controllers.SessionManagerControl(parent, **params)[source]#

Session Manager

Session file (Parameter)

Load session (Action)

Reset session (Action)

Additional GUI elements on: