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from __future__ import division
import os
import numpy as np
import pandas as pd
#import lmfit
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%matplotlib inline
import matplotlib.pyplot as plt
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d = {}
for bsearch_ph_sel in ['all-ph', 'Dex', 'AND-gate']:
data_file = 'results/usALEX-5samples-PR-raw-%s.txt' % bsearch_ph_sel
d[bsearch_ph_sel] = pd.read_csv(data_file, sep="\s+").set_index('sample')[['E_pr_fret_kde']]
#d[bsearch_ph_sel].columns = [bsearch_ph_sel]
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fig, ax = plt.subplots()
for bs, data in d.items():
data.plot(label=bs, ax=ax)
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(d['AND-gate'] - d['all-ph']).abs().max()*100
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(d['AND-gate'] - d['Dex']).abs()
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(d['all-ph'] - d['Dex']).abs().max()*100
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d['Dex']
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#bsearch_ph_sel = 'all=ph'
#bsearch_ph_sel = 'AND-gate'
bsearch_ph_sel = 'Dex'
data_file = 'results/usALEX-5samples-PR-raw-%s.txt' % bsearch_ph_sel
These are the RAW proximity ratios for the 5 samples (only background correction, no leakage nor direct excitation):
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data_raw = pd.read_csv(data_file, sep="\s+").set_index('sample')
data_raw[['E_pr_fret', 'E_pr_fret_kde']]
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leakage_coeff_fname = 'results/usALEX - leakage coefficient DexDem.txt'
leakage = np.loadtxt(leakage_coeff_fname)
print 'Leakage coefficient:', leakage
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dir_ex_t_datasheet_fname = 'results/Dyes - ATT0647N-ATTO550 abs X-section ratio at 532nm.txt'
dir_ex_t_datasheet = np.loadtxt(dir_ex_t_datasheet_fname)
print 'Direct excitation (dir_ex_t) from datasheet:', dir_ex_t_datasheet
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gamma_coeff_fname = 'results/usALEX - gamma factor - all-ph.txt'
gamma = np.loadtxt(gamma_coeff_fname)
print 'Gamma factor:', gamma
And these are the FRET efficiencies fitted from corrected histograms for the same 5 samples:
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data_file = 'results/usALEX-5samples-E-corrected-all-ph.txt'
data_corr = pd.read_csv(data_file, sep="\s+").set_index('sample')
data_corr[['E_pr_fret', 'E_pr_fret_kde']]
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The expression to convert RAW PR values to corrected FRET efficiencies:
$$ E = \frac{E_{R} \left(L_{k} + d_{exT} \gamma + 1\right) - L_{k} - d_{exT} \gamma}{E_{R} \left(L_{k} - \gamma + 1\right) - L_{k} + \gamma}$$See Derivation of FRET and S correction formulas for the derivation.
We load FRETBursts software that provides this function (as fretmath.correct_E_gamma_leak_dir):
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%run load_fretbursts.py --nogui
Using datasheet values for $d_{exT}$ we the following FRET efficiencies:
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E_datasheet = fretmath.correct_E_gamma_leak_dir(data_raw.E_pr_fret_kde,
leakage=leakage,
dir_ex_t=dir_ex_t_datasheet,
gamma=gamma)*100
E_datasheet
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out = data_corr[['E_pr_fret_kde']].copy()*100
out.columns = ['E_alex']
out['E_datasheet'] = E_datasheet
out
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out.plot(alpha=0.4, lw=3, style=dict(E_alex='-ob', E_datasheet='-sr'));
NOTE: The corrected FRET efficiencies using the datasheet and μs-ALEX-based direct excitation do not match well.
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import lmfit
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def residuals_absolute(params, E_raw, E_ref):
dir_ex_t = params['dir_ex_t'].value
return E_ref - fretmath.correct_E_gamma_leak_dir(E_raw,
leakage=leakage,
gamma=gamma,
dir_ex_t=dir_ex_t)
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def residuals_relative(params, E_raw, E_ref):
dir_ex_t = params['dir_ex_t'].value
return (E_ref - fretmath.correct_E_gamma_leak_dir(E_raw,
leakage=leakage,
gamma=gamma,
dir_ex_t=dir_ex_t))/E_ref
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params = lmfit.Parameters()
params.add('dir_ex_t', value=0.05)
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m = lmfit.minimize(residuals_absolute, params, args=(data_raw.E_pr_fret_kde, data_corr.E_pr_fret_kde))
lmfit.report_fit(m.params, show_correl=False)
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m = lmfit.minimize(residuals_relative, params, args=(data_raw.E_pr_fret_kde, data_corr.E_pr_fret_kde))
lmfit.report_fit(m.params, show_correl=False)
NOTE: The fitted
dir_ex_tis XX% as opposed to 10.6% as expected from the absorption spectra of ATTO550 and ATTO647 at 532nm.
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m.params['dir_ex_t'].value
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with open('results/usALEX - leakage coefficient dir_ex_t.txt', 'w') as f:
f.write(str(m.params['dir_ex_t'].value))
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