lingress

Lingress

Lingress项目是一项旨在利用单变量线性回归模型的简化管道来开发用于分析核磁共振（NMR）数据集的流线管道。该软件包包括通过普通最小二乘法（OLS）方法的线性回归分析的执行，并提供了结果数据的视觉解释。值得注意的是，它在其分析范围中包括所有NMR峰的P值。

从功能上讲，该程序通过应用线性回归努力拟合代谢概况模型。它的设计和能力为代谢研究领域中的深入和细微的数据分析提供了强大的工具。

如何安装

pip install lingress

UI峰采摘

 #Example data
import numpy as np
from lingress import pickie_peak
import pandas as pd


df = pd . read_csv ( "https://raw.githubusercontent.com/aeiwz/example_data/main/dataset/Example_NMR_data.csv" )
spectra = df . iloc [:, 1 :]
ppm = spectra . columns . astype ( float ). to_list ()


#defind plot data and run UI
pickie_peak ( spectra = spectra , ppm = ppm ). run_ui ()

线性回归模型

 import pandas as pd
from lingress import lin_regression


df = pd . read_csv ( "https://raw.githubusercontent.com/aeiwz/example_data/main/dataset/Example_NMR_data.csv" )
X = df . iloc [:, 1 :]
ppm = spectra . columns . astype ( float ). to_list ()
y = df [ 'Group' ]


mod = lin_regression ( x = X , target = y , label = y , features_name = ppm , adj_method = 'fdr_bh' )
mod . create_dataset ()
mod . fit_model ()

 mod . spec_uniplot ()

 mod . volcano_plot ()

 mod . resampling ( n_jobs = - 1 , n_boots = 100 , adj_method = 'fdr_bh' )

 [Parallel(n_jobs=-1)]: Using backend LokyBackend with 8 concurrent workers.
[Parallel(n_jobs=-1)]: Done   6 tasks      | elapsed:    3.7s
[Parallel(n_jobs=-1)]: Done  60 tasks      | elapsed:    6.7s
[Parallel(n_jobs=-1)]: Done 150 tasks      | elapsed:   11.2s
[Parallel(n_jobs=-1)]: Done 276 tasks      | elapsed:   17.8s
...
[Parallel(n_jobs=-1)]: Done 6486 tasks      | elapsed:  5.6min
[Parallel(n_jobs=-1)]: Done 7188 tasks      | elapsed:  6.1min
[Parallel(n_jobs=-1)]: Done 7211 out of 7211 | elapsed:  6.1min finished

 mod . resampling_df ()

p值	STD P值	beta系数	STD Beta	平均P值（F检验）	STD P值（F检验）	平均R平方	STD R-Square	R2	STD R平方调整	q_value
0.60075	3.575454E-03	1.610523E-02	3.673194E+06	502596.020205	0.434302	0.276809	0.138650	0.156244	0.030981	4.012856E-03
0.60125	2.327687E-04	6.418472E-04	4.208365E+06	638734.119190	南	南	0.160225	0.175463	0.056503	3.531443E-04
0.60175	1.511846E-04	3.690541E-04	4.776924E+06	582175.023885	0.272894	0.258094	0.250765	0.204542	0.157111	2.443829E-04
0.60225	2.724337E-04	7.138873E-04	4.45084e+06	624407.676115	0.132108	0.188570	0.379931	0.198055	0.302422	4.037237E-04
0.60275	2.271675E-04	5.238926E-04	3.596622E+06	643161.588649	0.030732	0.056968	0.558447	0.158948	0.503253	3.458106E-04
...	...	...	...	...	...	...	...	...	...	...
4.20375	2.542707E-09	1.077483E-08	2.231841E+07	479783.299949	南	南	0.099255	0.130321	-0.010838	4.472063E-08
4.20425	4.727199E-10	1.269310E-09	2.201865E+07	631164.491894	0.420162	0.308196	0.163733	0.184153	0.059199	1.940690E-08
4.20475	1.710447E-09	4.659603E-09	2.285026E+07	721568.566334	南	南	0.100927	0.138527	-0.010207	3.595928E-08
4.20525	1.043658E-08	9.454456E-08	2.449345E+07	287615.593479	0.310386	0.301403	0.263740	0.245996	0.171707	1.084412E-07
4.20575	1.606948E-08	1.123188E-07	2.621135E+07	246414.620688	0.242344	0.257300	0.299881	0.244772	0.212366	1.457572E-07