rda-package 1.0.0

rhythmic data analysis package

Rhythmic Data Analysis

Include different functions that allow the user to perform rhythmic data analysis (LS, ARS, JTK, Cosinor, RAIN).

Installation

Can be installed with pip :

pip install rda-package

Then you can import the package with :

from rda_package import rda

The 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 sklearn

To 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")

Functions

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.