In [1]:
# Visualize Figure 1b
# Jackson M. Tsuji, 2023
In [2]:
import pandas as pd
from plotnine import *
from scipy.signal import find_peaks
from collections import namedtuple
from numpy import linspace
In [3]:
def load_hplc_pda_data(pda_filepath, pre_processed=False):
if pre_processed is False:
hplc_profile_data = pd.read_csv(pda_filepath, sep='\t', skiprows=[0,1,2,3,4,5,6,7,8,10,11,12,13,14,15,16,17,18],
encoding_errors='replace')\
.rename(columns={'WAVE.TABLE':'Retention time (min)'})
elif pre_processed is True:
hplc_profile_data = pd.read_csv(pda_filepath, sep='\t')
else:
raise ValueError(f'pre_processed must be True or False, but you provided {pre_processed}')
return(hplc_profile_data)
def tabulate_peaks(data_table, signal_col_name, ref_col_name, prominence):
peak_pos, _ = find_peaks(data_table[signal_col_name].to_numpy(), prominence=prominence)
peak_ref_values = data_table[ref_col_name][peak_pos]
peak_heights = data_table[data_table[ref_col_name].isin(peak_ref_values)][signal_col_name]
peak_table = pd.DataFrame({ref_col_name:peak_ref_values, signal_col_name:peak_heights})
return(peak_table)
def tabulate_spectra(hplc_profile_data, retention_times, round_digits=None):
spectra_data = hplc_profile_data[hplc_profile_data['Retention time (min)'].isin(retention_times)]\
.set_index('Retention time (min)')\
.transpose()\
.reset_index()\
.rename(columns={'index':'Wavelength (nm)'})\
.melt(id_vars='Wavelength (nm)', value_name='Absorbance (A.U.)')
spectra_data = spectra_data.astype({'Wavelength (nm)':'int64', 'Retention time (min)':'float64'})
if round_digits is not None:
spectra_data['Retention time (min)'] = spectra_data['Retention time (min)'].round(round_digits)
return(spectra_data)
In [4]:
def process_hplc_data(pda_filepath, wavelength, provinence_profile=2000, provinence_spectrum=90000, pre_loaded_pda=False):
wavelength = str(wavelength)
# Load data
if pre_loaded_pda is False:
hplc_profile_data = load_hplc_pda_data(pda_filepath)
else:
hplc_profile_data = pda_filepath # assumes a pandas df of the correct format was passed in
# Get peaks
peaks = tabulate_peaks(hplc_profile_data, wavelength, 'Retention time (min)', provinence_profile)
print('Identified ' + str(peaks.shape[0]) + ' peaks in HPLC profile at ' + wavelength + ' nm')
profile_plot = (ggplot(hplc_profile_data, aes(x='Retention time (min)', y=wavelength))
+ geom_vline(xintercept=peaks['Retention time (min)'], linetype='dashed', colour='grey')
+ geom_path(size=0.8)
+ theme_bw()
+ theme(text=element_text(colour='black', family='Arial'),
panel_grid=element_blank())
+ ylab('Absorbance at ' + wavelength + ' nm (A.U.)')
)
# Get associated spectra with peaks
spectra = tabulate_spectra(hplc_profile_data, peaks['Retention time (min)'], round_digits=2)
spectra_plot = (ggplot(spectra, aes(x='Wavelength (nm)', y='Absorbance (A.U.)'))
+ geom_path()
+ facet_grid('Retention time (min) ~ .', scales='free_y')
+ theme_bw()
+ theme(text=element_text(colour='black', family='Arial'),
panel_grid=element_blank())
)
spectra_pre_plot = spectra.copy(deep=True)
spectra_pre_plot['Retention time (min)'] = spectra_pre_plot['Retention time (min)'].astype('str')
spectra_pre_plot['Retention time (min)'] = pd.Categorical(spectra_pre_plot['Retention time (min)'],
categories=spectra_pre_plot['Retention time (min)'].unique(), ordered=True)
spectra_overlay_plot = (ggplot(spectra_pre_plot, aes(x='Wavelength (nm)', y='Absorbance (A.U.)'))
+ geom_path(aes(group='Retention time (min)', colour='Retention time (min)'), alpha=0.8, size=1)
+ theme_bw()
+ theme(text=element_text(colour='black', family='Arial'),
panel_grid=element_blank())
)
# Get the spectrum associated with just the largest peak
max_peak_rt = peaks[peaks[wavelength] == peaks[wavelength].max()]['Retention time (min)']
spectra_max = tabulate_spectra(hplc_profile_data, max_peak_rt, round_digits=2)
# Get absorbance peaks
spectra_max_peaks = tabulate_peaks(spectra_max, 'Absorbance (A.U.)', 'Wavelength (nm)', provinence_spectrum)
print('Identified ' + str(spectra_max_peaks.shape[0]) + ' peaks in largest profile absorbance spectrum at ' + str(round(list(max_peak_rt)[0],2)) + ' min')
spectrum_max_plot = (ggplot(spectra_max, aes(x='Wavelength (nm)', y='Absorbance (A.U.)'))
+ geom_vline(xintercept=spectra_max_peaks['Wavelength (nm)'], linetype='dashed', colour='grey')
+ geom_path(size=0.8)
+ theme_bw()
+ theme(text=element_text(colour='black', family='Arial'),
panel_grid=element_blank())
)
hplc_output = namedtuple('hplc_output', ['tables','figures'])
table_output = namedtuple('table_output', ['profile','peaks','spectra','spectrum_max','spectrum_max_peaks'])
figure_output = namedtuple('figure_output', ['profile', 'spectra_align', 'spectra_overlay', 'spectrum_max'])
return(hplc_output(table_output(hplc_profile_data,peaks,spectra,spectra_max,spectra_max_peaks),
figure_output(profile_plot, spectra_plot, spectra_overlay_plot, spectrum_max_plot)))
In [5]:
# Load
caur_raw = load_hplc_pda_data('https://zenodo.org/records/10275618/files/Cfx-aurantiacus-HPLC-run1.tsv.gz', pre_processed=True)
cferro_raw = load_hplc_pda_data('https://zenodo.org/records/10275618/files/Chl-ferrooxidans-HPLC-run1.tsv.gz', pre_processed=True)
chx_raw = load_hplc_pda_data('https://zenodo.org/records/10275618/files/Ca-Chx-allophototropha-L227-S17-HPLC-run1.tsv.gz', pre_processed=True)
caur_raw.head()
Out[5]:
| Retention time (min) | 350 | 351 | 352 | 353 | 354 | 355 | 356 | 357 | 358 | ... | 791 | 792 | 793 | 794 | 795 | 796 | 797 | 798 | 799 | 800 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0.000 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1 | 0.011 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2 | 0.021 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3 | 0.032 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 4 | 0.043 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
5 rows × 452 columns
In [6]:
caur_processed = process_hplc_data(caur_raw, wavelength=667, provinence_profile=4000,
provinence_spectrum=90000, pre_loaded_pda=True)
caur_processed.figures
Identified 8 peaks in HPLC profile at 667 nm Identified 2 peaks in largest profile absorbance spectrum at 35.77 min
/Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:635: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning. /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/geoms/geom.py:231: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.
/Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:1231: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
Out[6]:
figure_output(profile=<ggplot: (385998666)>, spectra_align=<ggplot: (387923192)>, spectra_overlay=<ggplot: (387935939)>, spectrum_max=<ggplot: (387943224)>)
In [7]:
caur_processed.tables.peaks
Out[7]:
| Retention time (min) | 667 | |
|---|---|---|
| 63 | 0.672 | 2682 |
| 1193 | 12.725 | 11598 |
| 1294 | 13.803 | 10650 |
| 1588 | 16.939 | 5486 |
| 3353 | 35.765 | 366782 |
| 3959 | 42.229 | 72680 |
| 4222 | 45.035 | 13215 |
| 4427 | 47.221 | 249324 |
In [8]:
cferro_processed = process_hplc_data(cferro_raw, wavelength=667, provinence_profile=4000,
provinence_spectrum=90000, pre_loaded_pda=True)
cferro_processed.figures
Identified 15 peaks in HPLC profile at 667 nm Identified 2 peaks in largest profile absorbance spectrum at 31.1 min
/Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:635: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning. /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/geoms/geom.py:231: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.
/Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:1231: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
Out[8]:
figure_output(profile=<ggplot: (388267874)>, spectra_align=<ggplot: (388382058)>, spectra_overlay=<ggplot: (388396727)>, spectrum_max=<ggplot: (388249653)>)
In [9]:
cferro_processed.tables.peaks
Out[9]:
| Retention time (min) | 667 | |
|---|---|---|
| 59 | 0.629 | 2844 |
| 430 | 4.587 | 11314 |
| 2738 | 29.205 | 68000 |
| 2816 | 30.037 | 8400 |
| 2916 | 31.104 | 393115 |
| 3079 | 32.843 | 30684 |
| 3103 | 33.099 | 33018 |
| 3671 | 39.157 | 19042 |
| 3814 | 40.683 | 98407 |
| 3945 | 42.080 | 12986 |
| 4148 | 44.245 | 9884 |
| 4227 | 45.088 | 3319 |
| 4271 | 45.557 | 46627 |
| 4380 | 46.720 | 5608 |
| 4484 | 47.829 | 10522 |
In [10]:
chx_processed = process_hplc_data(chx_raw, wavelength=667, provinence_profile=1000,
provinence_spectrum=10000, pre_loaded_pda=True)
chx_processed.figures
Identified 12 peaks in HPLC profile at 667 nm Identified 2 peaks in largest profile absorbance spectrum at 39.18 min
/Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:635: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning. /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/facets/strips.py:216: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]` /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/geoms/geom.py:231: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.
/Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:1231: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
Out[10]:
figure_output(profile=<ggplot: (387913690)>, spectra_align=<ggplot: (388871157)>, spectra_overlay=<ggplot: (388892346)>, spectrum_max=<ggplot: (388892289)>)
In [11]:
chx_processed.tables.peaks
Out[11]:
| Retention time (min) | 667 | |
|---|---|---|
| 67 | 0.715 | 4235 |
| 76 | 0.811 | 3154 |
| 414 | 4.416 | 883 |
| 430 | 4.587 | 5801 |
| 2908 | 31.019 | 7760 |
| 3071 | 32.757 | 3625 |
| 3673 | 39.179 | 23385 |
| 3805 | 40.587 | 17775 |
| 4235 | 45.173 | 6162 |
| 4346 | 46.357 | 4567 |
| 4619 | 49.269 | 17404 |
| 4715 | 50.293 | 14344 |
In [12]:
hplc_profiles_merged = caur_raw[['Retention time (min)', '667']].rename(columns={'667': 'Cfx. aurantiacus'})\
.merge(cferro_raw[['Retention time (min)', '667']].rename(columns={'667': 'Chl. ferrooxidans'}), on='Retention time (min)', how='inner')\
.merge(chx_raw[['Retention time (min)', '667']].rename(columns={'667': 'Ca. Chx. allophototropha'}), on='Retention time (min)', how='inner')
# Normalize based on max peak height
max1 = hplc_profiles_merged['Cfx. aurantiacus'].max()
max2 = hplc_profiles_merged['Chl. ferrooxidans'].max()
max3 = hplc_profiles_merged['Ca. Chx. allophototropha'].max()
hplc_profiles_merged['Chl. ferrooxidans'] = hplc_profiles_merged['Chl. ferrooxidans'] * max1 / max2
hplc_profiles_merged['Ca. Chx. allophototropha'] = hplc_profiles_merged['Ca. Chx. allophototropha'] * max1 / max3
# Offset
offset = max1 * 1.2
hplc_profiles_merged['Cfx. aurantiacus'] = hplc_profiles_merged['Cfx. aurantiacus'] + offset * 2
hplc_profiles_merged['Ca. Chx. allophototropha'] = hplc_profiles_merged['Ca. Chx. allophototropha'] + offset
hplc_profiles_merged = hplc_profiles_merged.melt(id_vars='Retention time (min)', var_name='Sample', value_name='Absorbance (A.U.)')
hplc_profiles_merged = hplc_profiles_merged[(hplc_profiles_merged['Retention time (min)'] > 25) & (hplc_profiles_merged['Retention time (min)'] < 55)]
hplc_profiles_merged['Sample'] = pd.Categorical(hplc_profiles_merged['Sample'], categories=['Cfx. aurantiacus', 'Ca. Chx. allophototropha', 'Chl. ferrooxidans'], ordered=True)
hplc_profiles_merged.head()
Out[12]:
| Retention time (min) | Sample | Absorbance (A.U.) | |
|---|---|---|---|
| 2344 | 25.003 | Cfx. aurantiacus | 880093.8 |
| 2345 | 25.013 | Cfx. aurantiacus | 880112.8 |
| 2346 | 25.024 | Cfx. aurantiacus | 880091.8 |
| 2347 | 25.035 | Cfx. aurantiacus | 880133.8 |
| 2348 | 25.045 | Cfx. aurantiacus | 880088.8 |
In [13]:
max_spectra = caur_processed.tables.spectrum_max.drop(columns='Retention time (min)').rename(columns={'Absorbance (A.U.)':'Cfx. aurantiacus'})\
.merge(cferro_processed.tables.spectrum_max.drop(columns='Retention time (min)').rename(columns={'Absorbance (A.U.)':'Chl. ferrooxidans'}), on='Wavelength (nm)', how='inner')\
.merge(chx_processed.tables.spectrum_max.drop(columns='Retention time (min)').rename(columns={'Absorbance (A.U.)':'Ca. Chx. allophototropha'}), on='Wavelength (nm)', how='inner')
# Normalize based on max peak height
max1 = max_spectra['Cfx. aurantiacus'].max()
max2 = max_spectra['Chl. ferrooxidans'].max()
max3 = max_spectra['Ca. Chx. allophototropha'].max()
max_spectra['Chl. ferrooxidans'] = max_spectra['Chl. ferrooxidans'] * max1 / max2
max_spectra['Ca. Chx. allophototropha'] = max_spectra['Ca. Chx. allophototropha'] * max1 / max3
# Offset
offset = max1 * 0.7
max_spectra['Cfx. aurantiacus'] = max_spectra['Cfx. aurantiacus'] + offset * 2
max_spectra['Ca. Chx. allophototropha'] = max_spectra['Ca. Chx. allophototropha'] + offset
max_spectra = max_spectra.melt(id_vars='Wavelength (nm)', var_name='Sample', value_name='Absorbance (A.U.)')
max_spectra['Sample'] = pd.Categorical(max_spectra['Sample'], categories=['Cfx. aurantiacus', 'Ca. Chx. allophototropha', 'Chl. ferrooxidans'], ordered=True)
max_spectra.head()
Out[13]:
| Wavelength (nm) | Sample | Absorbance (A.U.) | |
|---|---|---|---|
| 0 | 350 | Cfx. aurantiacus | 825746.0 |
| 1 | 351 | Cfx. aurantiacus | 823257.0 |
| 2 | 352 | Cfx. aurantiacus | 821346.0 |
| 3 | 353 | Cfx. aurantiacus | 820110.0 |
| 4 | 354 | Cfx. aurantiacus | 819418.0 |
In [14]:
profile_plot = (ggplot(hplc_profiles_merged, aes(x='Retention time (min)', y='Absorbance (A.U.)'))
+ geom_path(aes(group='Sample', colour='Sample'), alpha=0.8, size=0.8)
+ theme_bw()
+ theme(text=element_text(colour='black', family='Arial'),
panel_grid=element_blank(),
axis_text_y=element_blank(),
axis_ticks_major_y=element_blank(),
legend_key=element_blank(),
panel_border=element_rect(colour='black'))
+ scale_colour_manual(values=['#7570b3', '#d95f02', '#1b9e77'])
+ ylab('Absorbance at 667 nm (A.U.)')
)
profile_plot
/Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:1231: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
Out[14]:
<ggplot: (388883839)>
In [15]:
profile_plot.save('HPLC_profiles_667nm.pdf', width=70, height=70,
units='mm', verbose=False)
/Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:1231: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
In [16]:
spectra_plot = (ggplot(max_spectra, aes(x='Wavelength (nm)', y='Absorbance (A.U.)'))
+ geom_path(aes(group='Sample', colour='Sample'), alpha=0.8, size=0.8)
+ theme_bw()
+ theme(text=element_text(colour='black', family='Arial'),
panel_grid=element_blank(),
axis_text_y=element_blank(),
axis_ticks_major_y=element_blank(),
legend_key=element_blank(),
panel_border=element_rect(colour='black'))
+ scale_colour_manual(values=['#7570b3', '#d95f02', '#1b9e77'])
)
spectra_plot
/Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:1231: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
Out[16]:
<ggplot: (388360482)>
In [17]:
spectra_plot.save('HPLC_max_spectra_667nm.pdf', width=70, height=70,
units='mm', verbose=False)
/Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:1231: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead /Users/jmtsuji/miniconda3/envs/jupyterlab/lib/python3.12/site-packages/plotnine/utils.py:317: FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. Use isinstance(dtype, CategoricalDtype) instead
In [18]:
caur_processed.tables.spectrum_max_peaks
Out[18]:
| Wavelength (nm) | Absorbance (A.U.) | |
|---|---|---|
| 85 | 435 | 460215 |
| 317 | 667 | 366782 |
In [19]:
cferro_processed.tables.spectrum_max_peaks
Out[19]:
| Wavelength (nm) | Absorbance (A.U.) | |
|---|---|---|
| 85 | 435 | 485911 |
| 317 | 667 | 393115 |
In [20]:
chx_processed.tables.spectrum_max_peaks
Out[20]:
| Wavelength (nm) | Absorbance (A.U.) | |
|---|---|---|
| 85 | 435 | 28589 |
| 317 | 667 | 23385 |
In [ ]: