transcriptic.analysis

Kinetics

class transcriptic.analysis.kinetics.Spectrophotometry(datasets)

Bases: transcriptic.analysis.kinetics._Kinetics

A Spectrophotomery object is used to analyze a kinetic series of PlateRead datasets

properties

DataFrame – DataFrame of aliquot properties for each well, useful for groupby operations during plots

readings

DataFrame – DataFrame of readings for each well at different time points

operation

str – Operation used for generating these growth curves (e.g. Absorbance)

plot(wells='*', groupby=None, title=None, xlabel=None, ylabel=None, max_legend_len=20)

This generates a plot of the kinetics curve. Note that this function is meant for use under a Jupyter notebook environment

Example Usage:

from transcriptic.analysis.kinetics import Spectrophotometry
growth_curve = Spectrophotometry(myRun.data.Datasets)
growth_curve.plot(wells=["A1", "A2", "B1", "B2"])
growth_curve.plot(wells=["A1", "A2", "B1", "B2"], groupby="row", title="Row Groups")
growth_curve.plot(wells=["A1", "A2", "B1", "B2"], groupby="name", ylabel="Absorbance Units")
growth_curve.plot(groupby="name", max_legend_len=40)
Parameters:
  • wells (Optional[list or str]) – If not specified, this plots all the wells associated with the Datasets given. Otherwise, specifiy a list of well indices ([“A1”, “B1”]) or a specific well (“A1”)
  • groupby (Optional[str]) – When specified, this groups the wells with the same property value together. On the plot, each group will be represented by a single curve with the mean values and error bars of 1 std. dev. away from the mean
  • title (Optional[str]) – Plot title. Default: “Kinectics Curve (run-id)”
  • xlabel (Optional[str]) – Plot x-axis label. Default: “Time”
  • ylabel (Optional[str]) – Plot y-axis label. Default: “Operation (Wavelength)”
  • max_legend_len – Maximum number of characters for the legend labels before truncating. Default: 20
Returns:

Plotly iplot object. Will be rendered nicely in Jupyter notebook instance

Return type:

IPlot

Imaging

class transcriptic.analysis.imaging.ImagePlate(dataset)

Bases: future.types.newobject.newobject

An ImagePlate object generalizes the parsing of datasets derived from the plate camera for easy visualization.

Parameters:dataset (dataset) – Single dataset selected from datasets object
raw

BytesIO – Raw buffer of image bytes

image

PIL.Image – Image object as rendered by PIL

display()

Displays the original full-sized image. Helpful when used in an IPython kernel

Returns:Returns a HTML iframe of the full-size image which is rendered nicely in IPython (if IPython is present)
Return type:HTML

Spectrophotometry

class transcriptic.analysis.spectrophotometry.Absorbance(dataset, group_labels, group_wells=None, control_abs=None, name=None)

Bases: transcriptic.analysis.spectrophotometry._PlateRead

An Absorbance object parses a dataset object and provides functions for easy statistical analysis and visualization.

Parameters:
  • dataset (dataset) – Single dataset selected from datasets object
  • group_labels (list[str]) – Labels for each of the respective groups
  • group_wells (list[int]) – List of list of wells (robot form) belonging to each group in order. E.g. [[1,3,5],[2,4,6]]
  • control_abs (Absorbance object, optional) – Absorbance object of water/control blank. If specified, will create adjusted dataframe df_adj by subtracting from existing df
  • name (str, optional) – Name of absorbance object. Used in plotting functions
beers_law(conc_list=None, use_adj=True, **kwargs)

” Apply Beer-Lambert’s law to a series of absorbance readings and get an estimation of the linearity between the absorbance and concentration values.

Parameters:
  • conc_list (list[double], optional) – List of concentrations of dye used
  • use_adj (Boolean, optional) – Booelan option which determines if the adjusted absorbance readings are used
  • **plot_kwargs (dict) – Optional dictionary of specifications for your plot type of choice
class transcriptic.analysis.spectrophotometry.Fluorescence(dataset, group_labels, group_wells=None, control_fluor=None, name=None)

Bases: transcriptic.analysis.spectrophotometry._PlateRead

An Fluorescence object parses a dataset object and provides functions for easy statistical analysis and visualization.

Parameters:
  • dataset (dataset) – Single dataset selected from datasets object
  • group_labels (list[str]) – Labels for each of the respective groups
  • group_wells (list[int]) – List of list of wells (robot form) belonging to each group in order. E.g. [[1,3,5],[2,4,6]]
  • control_fluor (Fluorescence object, optional) – Fluorescence object of water/control blank. If specified, will create adjusted dataframe df_adj by subtracting from existing df
  • name (str, optional) – Name of fluorescence object. Used in plotting functions
class transcriptic.analysis.spectrophotometry.Luminescence(dataset, group_labels, group_wells=None, control_lumi=None, name=None)

Bases: transcriptic.analysis.spectrophotometry._PlateRead

An Luminescence object parses a dataset object and provides functions for easy statistical analysis and visualization.

Parameters:
  • dataset (dataset) – Single dataset selected from datasets object
  • group_labels (list[str]) – Labels for each of the respective groups
  • group_wells (list[int]) – List of list of wells (robot form) belonging to each group in order. E.g. [[1,3,5],[2,4,6]]
  • control_lumi (Luminescence object, optional) – Luminescence object of water/control blank. If specified, will create adjusted dataframe df_adj by subtracting from existing df
  • name (str, optional) – Name of luminescence object. Used in plotting functions
transcriptic.analysis.spectrophotometry.compare_standards(pr_obj, std_pr_obj)

Compare a sample plate read object with a standard plate read object to get measures such as the Root-Mean-Square-Error (RMSE) and Coefficient-of-Variation (CV).

Parameters:
  • pr_obj (_PlateRead) – Sample plate read object
  • std_pr_obj (_PlateRead) – Standard plate read object