Include different functions that allow the user to perform rhythmic data analysis (LS, ARS, JTK, Cosinor, RAIN).
Can be installed with pip :
pip install rda-packageThen you can import the package with :
from rda_package import rdaThe setup.cfg file install automatically the dependencies necessary for the proper functioning of the package.
Otherwise, if the dependencies do not install automatically, you must manually install them :
pip install numpy
pip install pandas
pip install plotly
pip install rpy2
pip install CosinorPy
pip install matplotlib
pip install matplotlib_venn
pip install seaborn
pip install statsmodels
pip install sklearnTo finish, don't forget to install R if it's not already installed : https://cran.r-project.org/bin/windows/base/ ...and MetaCycle : https://github.com/gangwug/MetaCycle
# install 'devtools' in R(>3.0.2)
install.packages("devtools")
# install MetaCycle
devtools::install_github('gangwug/MetaCycle')...and Rain too : https://www.bioconductor.org/packages/release/bioc/html/rain.html
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("rain")cycMouseLiverRNA(filename):
Save MetaCycle dataset cycMouseLiverRNA.
cycMouseLiverProtein(filename):
Save MetaCycle dataset cycMouseLiverProtein.
menetRNASeqMouseLiver(filename):
Save RAIN dataset menetRNASeqMouseLiver.
meta2d_format(filename,sep=','):
Try format a given file to be usable with meta2d.
meta2d(filename,filestyle='csv',timepoints='line1',models=["ARS", "JTK", "LS"]):
Perform meta2d analysis (JTK, LS and/or, if no replicates, ARS) and store the result in the metaout folder.
cosinorpy(filename,sep=',', n_components = [1,2,3], period = 24, folder=None, **kwargs):
Perform Cosinor analysis and store the result in the cosinorpyout folder.
cosinor1py(filename,sep=',', period = 24,folder=None):
Perform 1 component Cosinor analysis and store the result in the cosinorpyout folder.
cosinor_pop(filename,sep,period):
Perform Cosinor analysis for population data and store the result in the cosinorpyout folder.
rain(filename,sample_rate=1,n_replicate=1,period=24):
Perform RAIN analysis and store the result in the rainout folder.
periodogram(df):
Plot the periodogram of a given dataset in cosinor format.
plot_meta2d(filename,pvalue_plot=False,amplitude_plot=False,period_plot=False,qvalue_plot=False,phase_plot=False):
Plot meta2d result in downloadable graphic table.
pv_load(filename):
Find all models p-values and save them in one file.
pv_dist(filename):
Plot and save in images folder p-values distributions.
pv_venn(filename):
Plot and save in images folder venn diagram using p-values.
qv_load(filename):
Find all models q-values and save them in one file.
qv_dist(filename):
Plot and save in images folder q-values distributions.
qv_venn(filename):
Plot and save in images folder venn diagram using q-values.
synt_rhythmic_data(filename,half_rnd=False,n_test=1,n_components=1,noise=0.5,replicates=1):
Create test data. (rhythmic)
synt_random_data(filename,n_test=1,replicates=1):
Create random test data. (non-rhythmic)
make_metrics(filename,y=None,half_rnd=False,conf_matrix=True,pvalue=False,qvalue=True):
Make metrics of an analyzed file.
plot_metrics(filename,qvalue=True,pvalue=False):
Plot metrics comparaison of ARS,JTK,LS,Meta2d,Cosinor,Rain.
file_rda(filename,filestyle='csv',metrics=False,half_rnd=True,n_components=3,replicates=1,sample_rate=2,period=24,y=None,pvalue=False,qvalue=True):
Perform meta2d,ARS,JTK,LS,Rain,Cosinor, make pv distribution, venn diagram and can plot metrics.
cosinor_read(filename,sep='\t'):
Read file in cosinor format, xlsx, csv or txt.
export_csv(df,filename):
Write a dataframe in a csv in cosinor format.
plot_data(df,filename=None):
Plot file or dataframe data.
cosinor_peaks(df,filename):
Plot cosinor peaks of an analysed file.
analysis(df,filename,lines='all',dt=None,time_unit_label='hours',T_cutoff = None):
pyBOAT signal analysis.
plot_detrend(x,y,deg=[1,2,3,5]):
Plot detrend ploynomial curve.
detrend(x,y,deg):
Detrend data using polynomial curve of a given degree.