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