Tecan OD Analyzer

Description

tecan_od_analyzer is a Python package for analysing optical density (OD) measurements taken from the Tecan Nano plate reader.

The tool parses the individual xlsx files from the plate reader and merges them into a single xlsx file using the autoflow_parse library. The merged file is read as a dataframe and every sample is labelled according to the calc.tsv file, provided by the user. The labelling helps to differentiate the sample purpose, indeed, some samples correspond to growth rate estimation and plotting while others are used to estimate the volume loss.

Once the samples are labelled according to the experiment, the volume loss throughout the culture is estimated and its effect is neutralized using a simple regression model. The next step concerns the outlier detection and growth phase estimation, which are done by using the croissance package. Subsequently, growth rate plots and summary statistics are also computed. The library also provides the functionality of interpolating OD measurements on processed samples at any given time.

Installation

Installation using pip

pip install tecan_od_analyzer

Installation from GitHub using pip

pip install git+https://github.com/biosustain/AutoFlow-HTC

Usage

tecan_od_analyzer can be used from the command-line by executing it in the directory where the xlsx files are located. The outputs will be gathered on a new directory called “results”.

Command line usage

Standard usage :

tecan_od_analyzer

The default command produces growth phase estimation, summary statistics on the estimations and growth rate plots split only by species. By default the volumess loss correction is computed.

Options :

tecan_od_analyzer --resultsdir RESULTSDIR specifies where the result will be redirected can be a directory name or a path.

tecan_od_analyzer --path PATH specifies where the data is, without the option the program runs in the path where it is executed.

tecan_od_analyzer --estimations Outputs only estimations for every sample in a text file.

tecan_od_analyzer --figures Outputs only the growth curves.

tecan_od_analyzer --summary Outputs only the estimations for every species and bioshaker as well as boxplots of the growth rare annotation parameters.

tecan_od_analyzer --individual Outputs the growth curves for every sample individually.

tecan_od_analyzer --bioshaker Splits the visualization of the growth rate plots according to the bioshaker and colors them by species.

tecan_od_analyzer --bioshakercolor Splits the visualization of the growth rate plots according to species and does not color them by bioshaker.

tecan_od_analyzer --interpolationplot Outputs Growth rate curves instead of scatter plots.

tecan_od_analyzer --interpolation Computes interpolation of samples given the measure time and outputs an xlsx file with the estimations.

tecan_od_analyzer --volumeloss This option allows the user to not compute the volume loss correction. By default, the volume loss correction is always computed.

tecan_od_analyzer --exportsvg With this option, plots will be saved as .svg rather than .png files. This is preferred if they are intended for a publication and allows for modifications in Illustrator.

tecan_od_analyzer --onlyspecies Splits the visualization of the growth rate plots according to species and bioshaker.

tecan_od_analzer --legendoff Disables display of the legend in plots.

Input

Standard required input

In order to run the program the user has to execute it where the data is. The inputs to the program correspond to the ones required for the autoflow_parser (log file, xlsx file, etc).

Furthermore, to classify the samples, a file where the purpose of each sample figures is needed. This file must be a tab-separated file (.tsv) with the following format :

Sample_ID	gr_calc	vl_calc	Species	Drop_out
BS1.A1	TRUE	FALSE		TRUE
BS1.A2	FALSE	TRUE		FALSE
…	…	…	…	…

It is important that the headers of every column must be written as it can be seen in the table. Concerning the Sample_ID, the bioshaker must appear at the beggining of the string.

OD interpolation required input

To compute the estimations the user must provide a tsv file named as od_measurements.tsv with the following format :

Sample_ID	Time	Regression_used
BS1.A1_	0.9	well
BS1.A2_	0.02	mean
…	…	…

For the regression column, two options are possible. On the first hand, the welloption corresponds to interpolate a given OD using only the data of the corresponding well/sample. On the second hand, the meanoption computes the interpolation using all the samples that share the same species and bioshaker.

It’s relevant to remark, that the numbers appearing in the time column must be written with dots and not with commas. The unit for the time column corresponds to hours. The sample_ID must be followed by the species ID.

Plotting options

The plots can be customized by selecting how to group the samples and combine them on a single plot. By default, the generated plot will contain all the samples within the same species in one plot. The plots can also be generated separately and split or color labelled by bioshaker. Also, the legends can be disabled which might come in handy if a lot of different strains are displayed. The output images can be generated as .png or .svg files.

The different options can be consulted by typing : tecan_od_analyzer --help or tecan_od_analyzer -h

Results

It must be noted that all the time units will appear in hours. The Results directory contains an example of the data obtained by running the program with the following command : tecan_od_analyzer -bc

Figures

• Plot of volume loss correlation against the time.

lm_volume_loss.png

• Growth rate measurements according to the specified options.

The name will change depending on the plotting option. It usually contains the sample ID and the bioshaker.

• Boxplots of the linear phase parameters for splitted by species

and bioshakers. Some of the parameters are the intercept, the beggining and end of the linear phase, slope, etc.

Estimations / Linear phase estimations

• Linear phase annotations annotations.xlsx file containing the

linear phase estimated parameters for all samples. - errors.txt file containing the list of samples for which the linear phase estimation resulted in an error. - Data_series.xlsx file containing all the data points after dilution and volume loss correction. The outliers have also been removed.

Summary statistics

• summary_stats.xlsx file containing summary statistics of the

estimated parameters grouping by species, by bioshaker and both.

Temporary growth rate calculation

• A temporary alternative is provided until the underlying issue

with the implemented growth rate calculation is fixed. The specific growth rates between every time step are calculated and provided in an .xlsx file and the progression of specific growth rates is plotted for every well. These files can be found in the Temporary_GR_check folder in the produced Results folder.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT

Credits

This autoflow_parser part of the package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

https://github.com/audreyr/cookiecutter-pypackage

tecan_od_analyzer methods

Main module.

tecan_od_analyzer.tecan_od_analyzer.argument_parser(argv_list=None)

Asesses the input arguments and outputs flags to run the different

functions according to the user needs.

Parameters

• argv_list – List of arguments provided by the user when running the

• program. –

Returns

flags

tecan_od_analyzer.tecan_od_analyzer.compensation_lm(cor_df, df_gr, df_vl600, flag_svg=False, flag_loff=False)

Given the correlation between volume and time, a linear model is built and plotted, the correction is applied to the growth measurements using the linear model, returns a figure with the LM and a dataframe with the corrected growth rate measurements.

Parameters

• df_gr – dataframe containing only growth rate measurements and

• time in hours. (differential) –

• cor_df – dataframe containing correlation measures between volume loss

• time for different bioshakers. (and) –

Returns

figure representing the linear model between the correlation and the time for every bioshaker. df_gr_comp_out: dataframe containing corrected growth rate measurements and differential time in hours.

Return type

fig

tecan_od_analyzer.tecan_od_analyzer.estimation_writter(df_data_series, df_annotations, error_list)

Writes a xlsx file with the estimations for every sample and outputs the errors on a log file.

Parameters

• df_data_series – dataframe containing the time series without outliers. df_annotations: dataframe containing the annotations of the linear phase.

• error_list – list containing the non-estimated samples by croissance

• to noisy data (due) –

Returns

file containing the estimations and IDs annotations_xlsx_file: file containing the data series and IDs without outliers of the non-estimated samples log_file: file containing the non estimated samples

Return type

series_xlsx_file

tecan_od_analyzer.tecan_od_analyzer.exponential(x, intercep, slope, n0)

Calculates the od for a given time with the parameters estimated with the croissance package

tecan_od_analyzer.tecan_od_analyzer.gr_estimation(df_gr_final)

removes outliers for every sample and outputs growth rate estimates for every given sample ID as a text file

Parameters

• df_gr_final – dataframe containing growth rate measurements and

• time in hours. (differential) –

Returns

List of growth rate estimations for every sample in df_gr_final errors: due to croissance noise handling some samples can not be estimated and list of series is returned for every non-estimated sample

Return type

estimations

tecan_od_analyzer.tecan_od_analyzer.gr_plots(df, sample, interpolationplot, color_=None, ind=False, legend_='bioshaker', title_='species', separate_species=False, flag_svg=False, flag_loff=False)

Generates a growth curve plot for a given series for common species, returns the plot.

Parameters

• df – dataframe containing differential times and OD measurements

• sample – sample used

• ind – flag that indicates to output individual plots if True or merged

• by sample species if False (plots) –

Returns

object containing the figure plt.savefig: saving the figure as a png or svg file

Return type

fig

tecan_od_analyzer.tecan_od_analyzer.input_output(cmd_dir, path)

Interprets input arguments related to the path to the data and output directory Args: cmd_dir : Name of directory where output will be sent path : path where the data is

tecan_od_analyzer.tecan_od_analyzer.interpolation(od_measurements, df_annotations, mean_df_bs)

Interpolates the values of given od readings and returns growth rate measurements.

Parameters

• od_measurements – Dataframe containing the desired samples to estimate

• df_annotations – Dataframe containing growth rate annotations of every

• sample –

• mean_df_bs – Dataframe containing the growth rate annotations grouped

• common species and bioshaker (by) –

Returns

Returned estimated od measurements and if the prediction lies in the model’s range

Return type

od_measurements

tecan_od_analyzer.tecan_od_analyzer.parse_data()

Calls the autoflow_parser and returns a merged xlsx document with all the OD readings combined

tecan_od_analyzer.tecan_od_analyzer.read_xlsx(filename='results.xlsx')

Reads .xlsx file, returns a dataframe with relevant variables. The output of the parser is set to be “results.xlsx”, the default reads the mentioned file without any additional argument

tecan_od_analyzer.tecan_od_analyzer.reshape_dataframe(df_gr, flag_species=False, flag_bioshaker=False)

Collects the times belonging to every sample and creates a time column relative to a specific sample, returns the modified dataframe.

Parameters

• df_gr – dataframe containing growth rate measurements and differential

• in hours. (time) –

• species_flag – flag that corresponds to the presence of more than one

• species (True) –

Returns

if species_flag is False

df_gr: dataframe with differential time measurements in hours displayed horizontally (one column containing the time measurements and one column contaning the OD measurements PER SAMPLE).

if flag is True :

df_gr_final: dataframe with differential time measurements in hours displayed horizontally (one column containing the time measurements and one column contaning the OD measurements PER SAMPLE). df_gr_final_list: list of dataframes originated from df_gr_final and split by common sample species

tecan_od_analyzer.tecan_od_analyzer.sample_outcome(sample_file, df)

Uses an external file containing individual sample purposes, returns two classifed dataframes based on sample purposes and labelled by bioshaker.

Parameters

• sample_file – variable or string containing the name of the file and

• extension. (its) –

• df – dataframe obtained by using the read_xlsx method on the merged

• file. (xlsx) –

Returns

dataframe containing observations related to the microbial growth rate, labelled by bioshaker. df_vl: dataframe containing observations related to the volume loss estimation, labelled by bioshaker.

Return type

df_gr

tecan_od_analyzer.tecan_od_analyzer.stats_plot(summary_df, flag_svg=False)

Box plots of annotation growth rate parameters by species and bioshaker Args: summary_df : dataframe containing the annotation parameters Return: call: string with status of plots creation

tecan_od_analyzer.tecan_od_analyzer.stats_summary(df_annotations)

Generates a statistics summary of the growth rate annotations.

Parameters

df_annotations – dataframe containing growth rate annotations

Returns

dataframe containing the summary statistics

Return type

summary_df

tecan_od_analyzer.tecan_od_analyzer.time_formater(df)

Takes a dataframe and turns date and time variables into differential time in hours for every bioshaker, returns modified dataframe.

Parameters

df – dataframe with containing date and time measurements.

Returns

dataframe with differential time measurements in hours.

Return type

df_out

tecan_od_analyzer.tecan_od_analyzer.vol_correlation(df_vl)

Assess the volume loss with OD450 measurements and correlates the OD450 readings to time for every different bioshaker, returns a correlation dataframe.

Parameters

df_vl – dataframe containing only volume loss measurements.

Returns

dataframe containing correlation values of the volume loss according to time measurements.

Return type

cor_df

Main module.

tecan_od_analyzer.autoflow_parser.autoflow_parser.check_results_files(entries: list, files: set, max_timeflex: int)

A function to check results files wrt logfile

tecan_od_analyzer.autoflow_parser.autoflow_parser.make_channel_dfs(merged_df: pandas.core.frame.DataFrame)

Make dataframes with only elapsed time (h) and samples for plotting

tecan_od_analyzer.autoflow_parser.autoflow_parser.merge_results(entry_to_file: dict, path: str)

Combine measurement dataframes into one

tecan_od_analyzer.autoflow_parser.autoflow_parser.parse_tecan_files(entry: str, file: str, path: str)

Method to parse tecan files and return pandas dataframe

tecan_od_analyzer.autoflow_parser.autoflow_parser.process_logfile(path: str)

Check logfile and return list of entries.

Console script for autoflow_parser.

tecan_od_analyzer.cli.cli.main(path, max_timeflex)

Console script for autoflow_parser.

Indices and tables

• Index

• Module Index

• Search Page