Analysis: 20250708
!pip install nucleus-cdk==0.5.0rc2 | tail -n2Requirement already satisfied: asttokens in /opt/homebrew/anaconda3/lib/python3.12/site-packages (from stack-data->ipython>=6.1.0->ipywidgets==8.*->jupyter-bokeh<5.0.0,>=4.0.5->nucleus-cdk==0.5.0rc2) (2.0.5)
Requirement already satisfied: pure-eval in /opt/homebrew/anaconda3/lib/python3.12/site-packages (from stack-data->ipython>=6.1.0->ipywidgets==8.*->jupyter-bokeh<5.0.0,>=4.0.5->nucleus-cdk==0.5.0rc2) (0.2.2)
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import warnings
from cdk.analysis.cytosol import platereader as pr
# Filter warnings
warnings.filterwarnings('ignore')
# Initialize plotting
pr.plot_setup()Load the data¶
Provide a CSV file containing the data, and a platemap. This function returns both the data with the plate map mapped to it, and the platemap by itself, which is useful for certain tasks.
data_file = "./20250708-cytation3-pure-timecourse-gfp-onepot-debug-01-pure-test-biotek-cdk.txt"
platemap_file = "./platemap.tsv"
data, platemap = pr.load_platereader_data(data_file, platemap_file)
data = data[data["Row"].isin(["B","D"])]Basic Analysis¶
Curves¶
Curves of RFU over time, by named sample.
pr.plot_curves(data, palette="colorblind");
plt.savefig("20250708-timeseries-exp1")
Steady state¶
Bar graph of steady-state endpoint of each sample. Steady state is calculated as the maximum fluorescence value over a 3-sample rolling average on the data.
pr.plot_steadystate(data, palette="colorblind");
plt.savefig("20250708-endpoint-exp1")
Kinetics¶
These functions calculate key kinetic parameters of the time series.
pr.plot_kinetics(data)PROVIDING AVERAGED KINETICS
(<seaborn.axisgrid.FacetGrid at 0x30c695f90>,
Velocity \
Time Data Max
Name Read
I + GFP-F-G35 0 days 01:29:05.429808396 1049.73 860.66
I + (2) GFP-F-G35 0 days 01:30:40.364387114 1435.89 1162.89
I - GFP-F-G35 0 days 01:23:31.932670691 1282.20 533.25
NEB deltaRibo GFP-F-G35 0 days 00:43:28.163799042 12754.87 17850.90
Negative GFP-F-G35 0 days 05:19:59.187903774 73.69 14.32
Positive GFP-F-G35 0 days 00:41:29.820518411 10364.40 15263.84
Lag \
Time Data
Name Read
I + GFP-F-G35 0 days 00:15:47.351645416 77.52
I + (2) GFP-F-G35 0 days 00:16:33.127954075 100.84
I - GFP-F-G35 -1 days +22:56:31.796438763 -517.01
NEB deltaRibo GFP-F-G35 0 days 00:00:34.069094534 261.44
Negative GFP-F-G35 0 days 00:11:10.534293992 34.96
Positive GFP-F-G35 0 days 00:00:38.870402567 635.25
Steady State \
Time Data
Name Read
I + GFP-F-G35 0 days 03:17:00.366196063 1994.48
I + (2) GFP-F-G35 0 days 03:19:47.672537712 2728.19
I - GFP-F-G35 0 days 04:59:57.109131835 2436.19
NEB deltaRibo GFP-F-G35 0 days 01:46:37.796190254 24234.26
Negative GFP-F-G35 0 days 12:54:37.432862693 140.01
Positive GFP-F-G35 0 days 01:41:38.157046348 19692.35
Fit \
params
Name Read
I + GFP-F-G35 [2099.457275310742, 1.6378385548318493, 1.4848...
I + (2) GFP-F-G35 [2871.778901675214, 1.619269160375266, 1.51121...
I - GFP-F-G35 [2564.4057203870493, 0.8226533295796935, 1.392...
NEB deltaRibo GFP-F-G35 [25509.742499961874, 2.7991337613446143, 0.724...
Negative GFP-F-G35 [147.38223773401128, 0.38866340751836903, 5.33...
Positive GFP-F-G35 [20728.792346311166, 2.9411432239019866, 0.691...
R^2 drift
Name Read
I + GFP-F-G35 1.00 207.96
I + (2) GFP-F-G35 1.00 238.89
I - GFP-F-G35 1.00 122.90
NEB deltaRibo GFP-F-G35 1.00 463.86
Negative GFP-F-G35 1.00 -3.00
Positive GFP-F-G35 1.00 306.21 )
We can also calculate the kinetics and display the parameters as a table.
pr.kinetic_analysis(data)Loading...