{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "# Real world example: Yeast Biolector Fermentation\n", "I this notebook, we will show how to apply the Pseudobatch transformation to data collected of a fed-batch experiment. We will showcase how to transform data from multiple cultures/replicates in one go and how to estimate the growth rate of each culture." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/s143838/.virtualenvs/pseudobatch-dev/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", " from .autonotebook import tqdm as notebook_tqdm\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "{'stan_version_major': '2', 'stan_version_minor': '29', 'stan_version_patch': '2', 'STAN_THREADS': 'false', 'STAN_MPI': 'false', 'STAN_OPENCL': 'false', 'STAN_NO_RANGE_CHECKS': 'false', 'STAN_CPP_OPTIMS': 'false'}\n" ] } ], "source": [ "import os\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import numpy as np\n", "import seaborn as sns\n", "from patsy import dmatrices\n", "import statsmodels.api as sm\n", "\n", "\n", "from pseudobatch import pseudobatch_transform_pandas\n", "from pseudobatch.datasets import load_real_world_yeast_fedbatch \n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "This data is from a cultivation experiment done in a Biolector (actually a Robolector) operating in fed-batch mode. Four different __S. cerevisiae__ strains were cultivated in 8 replicates, there only difference is when the individual culture was sampled and how many times samples were drawn. Thus the dataset contains a total of 32 growth curves. In this tutorial we will show how to use pseudobatch transformation to transform all 32 growth curves and how to estimate the growth rate for each replicate.\n", "\n", "The Biolector is capable of collect online biomass measurements through the light scatter sensor. Thus this dataset contains a biomass measurement for each approximately fifth minute.\n", "\n", "First, we will load the dataset which is a part of the `pseudobatch.datasets`, thus is is easily loaded." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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StrainBiolector wellBiolector columnBiolector rowCycleTimeFeeding timeVolumeAccum. feed [uL]Biomass concentration [light scatter]DO%Sample volume
0Yeast_strain_1C011C145.014.50280.2800.320.322.89147.4400020.0
1Yeast_strain_1C022C145.014.50280.2800.320.322.84146.2500000.0
2Yeast_strain_2C033C145.014.50280.2800.320.322.93145.4299930.0
3Yeast_strain_2C044C145.014.50280.2800.320.322.97145.6100010.0
4Yeast_strain_3C055C145.014.50280.2800.320.323.13148.2400050.0
\n", "
" ], "text/plain": [ " Strain Biolector well Biolector column Biolector row Cycle \n", "0 Yeast_strain_1 C01 1 C 145.0 \\\n", "1 Yeast_strain_1 C02 2 C 145.0 \n", "2 Yeast_strain_2 C03 3 C 145.0 \n", "3 Yeast_strain_2 C04 4 C 145.0 \n", "4 Yeast_strain_3 C05 5 C 145.0 \n", "\n", " Time Feeding time Volume Accum. feed [uL] \n", "0 14.5028 0.2 800.32 0.32 \\\n", "1 14.5028 0.2 800.32 0.32 \n", "2 14.5028 0.2 800.32 0.32 \n", "3 14.5028 0.2 800.32 0.32 \n", "4 14.5028 0.2 800.32 0.32 \n", "\n", " Biomass concentration [light scatter] DO% Sample volume \n", "0 2.89 147.440002 0.0 \n", "1 2.84 146.250000 0.0 \n", "2 2.93 145.429993 0.0 \n", "3 2.97 145.610001 0.0 \n", "4 3.13 148.240005 0.0 " ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fedbatch_df = load_real_world_yeast_fedbatch()\n", "fedbatch_df.head()" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "This dataset is preprocessed into a format that is very similar to the format of the simulated datasets used in the previous tutorials. This format follows the \"Tidy\"-format also called \"long-format\". Each row represent measurements of one culture at one time point. For example row 0 above hold the biomass, Volume, and Accumulated feed measurements etc of Biolector well C01 at feeding time 0.2 hours (time relative to feed initiation).\n", "\n", "To get started lets have look at the growth curves (light scatter measurements)." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# plotting\n", "g = sns.FacetGrid(fedbatch_df, col=\"Strain\", hue=\"Strain\", sharey=False)\n", "g.map_dataframe(sns.lineplot, data=fedbatch_df, x='Feeding time', y='Biomass concentration [light scatter]', units=\"Biolector well\", estimator=None)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "We don't see the discontinuities in these plots because the light scatter measurements are proportional to the concentration of biomass [1]. However, we cannot calculate the correct growth rate from the concentrations because the volume of the bioreactors (Biolector wells) is not constant. Thus, the changes in the biomass concentration is function of both growth and volume change. Luckily the pseudo batch transformation can alleviate this issue. \n", "\n", "To transform the data correctly, we have to apply the pseudobatch transformation to each culture (Biolector well). This can be done by using the `pseudobatch_transform_pandas()` with a groupby-apply approach.\n", "\n", "In the following code the the `.groupby()` method creates a separate dataframe for culture/Biolector well. Then the `.apply()` method supplies these dataframes one by one first argument in pseudobatch_transform_pandas function and collects the output from all of transformation in a series. The remaining arguments to the `pseudobatch_transform_pandas()` function are the same for each execution, notice that these arguments **HAVE TO** be given as **KEYWORD ARGUMENTS**, i.e. `argument_name=value`.\n", "\n", "Notice that the we use the `group_keys=False` argument in the groupby mehtod. This maintains the original index (order of the data), thus allowing us to write the pseudo batch transformed data directly back into the original dataframe.\n" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "biomass_concentration_in_feed = 0 # There is no yeast cells in the feed medium\n", "\n", "# Apply pseudobatch transformation and save the transformed biomass concentration in a new column\n", "fedbatch_df[[\"Biomass pseudo concentration\"]] = (fedbatch_df\n", " .groupby(\"Biolector well\", group_keys=False)\n", " .apply(pseudobatch_transform_pandas, \n", " measured_concentration_colnames=[\"Biomass concentration [light scatter]\"], # we wish to transform the biomass concentration measurements\n", " reactor_volume_colname='Volume',\n", " accumulated_feed_colname='Accum. feed [uL]',\n", " concentration_in_feed=[biomass_concentration_in_feed],\n", " sample_volume_colname='Sample volume',\n", " )\n", ")" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "Now that we have transformed the data we fit a log-linear model to each of the growth curve. Similar to previous tutorials we define a small helper function to fit the model." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "def fit_ols_model(formula_like: str, data: pd.DataFrame) -> sm.regression.linear_model.RegressionResultsWrapper:\n", " y, X = dmatrices(formula_like, data)\n", " model = sm.OLS(endog=y, exog=X)\n", " res = model.fit()\n", " return res" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "We can now iterate through the data from Biolector well and estimate the growth rate." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "growth_rate_models = {}\n", "for grp, dat in fedbatch_df.groupby(['Strain', 'Biolector well']):\n", " growth_rate_models[grp] = fit_ols_model('np.log(Q(\"Biomass pseudo concentration\")) ~ Q(\"Feeding time\")', dat)\n", "\n", "# collect the growth rates in a dataframe\n", "growth_rates_df = pd.DataFrame(\n", " [\n", " [strain, well, mod.params[1]] for (strain, well), mod in growth_rate_models.items()\n", " ], \n", " columns=['Strain', 'Biolector well', 'Growth rate']\n", ")" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "Finally, we can inspect estimated growth rates for each of cultures." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "([0, 1, 2, 3],\n", " [Text(0, 0, 'Yeast_strain_1'),\n", " Text(1, 0, 'Yeast_strain_2'),\n", " Text(2, 0, 'Yeast_strain_3'),\n", " Text(3, 0, 'Yeast_strain_4')])" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.catplot(data=growth_rates_df, x='Strain', y='Growth rate', hue='Strain', palette='colorblind')\n", "plt.xticks(rotation=45)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "We can see that strains 1, 2, and 3 have similar growth rates, while strain 4 appears to grow a little slower. In this example we showed how to use the pseudobatch transformation to transform real world data." ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## References\n", "[1] Kensy, Frank, Emerson Zang, Christian Faulhammer, Rung-Kai Tan, and Jochen Büchs. “Validation of a High-Throughput Fermentation System Based on Online Monitoring of Biomass and Fluorescence in Continuously Shaken Microtiter Plates.” Microbial Cell Factories 8, no. 1 (December 2009): 31. https://doi.org/10.1186/1475-2859-8-31.\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3.8.5 ('.venv_fedbatch-data-correction': venv)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.8" }, "orig_nbformat": 4, "vscode": { "interpreter": { "hash": "0337f5dfa8bf2ee335f62d4679bbb5183dd2c214a8c6ed07ec0592e911fc9b16" } } }, "nbformat": 4, "nbformat_minor": 2 }