I/O, file reading and writing, core formats (thunor.io)

class thunor.io.HtsPandas(doses, assays, controls)

High throughput screen dataset

Represented internally using pandas dataframes

Parameters:

  • doses (pd.DataFrame) – DataFrame of doses

  • assays (pd.DataFrame) – DataFrame of assays

  • controls (pd.DataFrame) – DataFrame of controls

cell_lines

List of cell lines in the dataset

Type:

list

drugs

List of drugs in the dataset

Type:

list

assay_names

List of assay names in the dataset

Type:

list

dip_assay_name

The assay name used for DIP rate calculations, e.g. “Cell count”

Type:

str

doses_unstacked()

Split multiple drugs/doses into separate columns

filter(cell_lines=None, drugs=None, plate=None)

Filter by cell lines and/or drugs

“None” means “no filter”

Parameters:

  • cell_lines (Iterable, optional) – List of cell lines to filter on

  • drugs (Iterable, optional) – List of drugs to filter on

  • plate (Iterable, optional) –

Returns:

A new dataset filtered using the supplied arguments

Return type:

HtsPandas

plate(plate_name, plate_size=384, include_dip_rates=False)

Return a single plate in PlateData format

Parameters:

  • plate_name (str) – The name of a plate in the dataset

  • plate_size (int) – The number of wells on the plate (default: 384)

  • include_dip_rates (bool) – Calculate and include DIP rates for each well if True

Returns:

The plate data for the requested plate name

Return type:

PlateData

class thunor.io.PlateData(width=24, height=16, dataset_name=None, plate_name=None, cell_lines=[], drugs=[], doses=[], dip_rates=[])

A High Throughput Screening Plate with Data

exception thunor.io.PlateFileParseException
class thunor.io.PlateMap(**kwargs)

Representation of a High Throughput Screening plate

Parameters:

kwargs (dict, optional) – Optionally supply “width” and “height” values for the plate

col_iterator()

Iterate over the column numbers in the plate

Returns:

Iterator over the column numbers (1, 2, 3, etc.)

Return type:

Iterator of int

property num_wells

Number of wells in the plate

classmethod plate_size_from_num_wells(num_wells)

Calculate plate size from number of wells, assuming 3x2 ratio

Parameters:

num_wells (int) – Number of wells in a plate

Returns:

Width and height of plate (numbers of wells)

Return type:

tuple

row_iterator()

Iterate over the row letters in the plate

Returns:

Iterator over the row letters (A, B, C, etc.)

Return type:

Iterator of str

well_id_to_name(well_id)

Convert a Well ID into a well name

Well IDs use a numerical counter from left to right, top to bottom, and are zero based.

Parameters:

well_id (int) – Well ID on this plate

Returns:

Name for this well, e.g. A1

Return type:

str

well_iterator()

Iterator over the plate’s wells

Returns:

Iterator over the wells in the plate. Each well is given as a dict of ‘well’ (well ID), ‘row’ (row character) and ‘col’ (column number)

Return type:

Iterator of dict

well_list()

List of the plate’s wells

Returns:

The return value of well_iterator() as a list

Return type:

list

well_name_to_id(well_name, raise_error=True)

Convert a well name to a Well ID

Parameters:

  • well_name (str) – A well name, e.g. A1

  • raise_error (bool) – Raise an error if the well name is invalid if True (default), otherwise return -1 for invalid well names

Returns:

Well ID for this well. See also well_id_to_name()

Return type:

int

thunor.io.read_hdf(filename_or_buffer)

Read a HtsPandas dataset from Thunor HDF5 format file

Parameters:

filename_or_buffer (str or object) – Filename or buffer from which to read the data

Returns:

Thunor HTS dataset

Return type:

HtsPandas

thunor.io.read_vanderbilt_hts(file_or_source, plate_width=24, plate_height=16, sep=None, _unstacked=False)

Read a Vanderbilt HTS format file

See the wiki for a file format description

Parameters:

  • file_or_source (str or object) – Source for CSV data

  • plate_width (int) – Width of the microtiter plates (default: 24, for 384 well plate)

  • plate_height (int) – Width of the microtiter plates (default: 16, for 384 well plate)

  • sep (str) – Source file delimiter (default: detect from file extension)

Returns:

HTS Dataset containing the data read from the CSV

Return type:

HtsPandas

thunor.io.write_hdf(df_data, filename, dataset_format='fixed')

Save a dataset to Thunor HDF5 format

Parameters:

  • df_data (HtsPandas) – HTS dataset

  • filename (str) – Output filename

  • dataset_format (str) – One of ‘fixed’ or ‘table’. See pandas HDFStore docs for details

thunor.io.write_vanderbilt_hts(df_data, filename, plate_width=24, plate_height=16, sep=None)

Read a Vanderbilt HTS format file

See the wiki for a file format description

Parameters:

  • df_data (HtsPandas) – HtsPandas - HTS dataset

  • filename (str or object) – filename or buffer to write into

  • plate_width (int) – plate width (number of wells)

  • plate_height (int) – plate height (number of wells)

  • sep (str) – Source file delimiter (default: detect from file extension)