File R-conMItion.spec of Package R-conMItion

# Automatically generated by CRAN2OBS
# 
# Spec file for package conMItion 
# This file is auto-generated using information in the package source, 
# esp. Description and Summary. Improvements in that area should be 
# discussed with upstream. 
# 
# Copyright (c) 2025 SUSE LINUX GmbH, Nuernberg, Germany. 
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# remain the property of their copyright owners, unless otherwise agreed 
# upon. The license for this file, and modifications and additions to the 
# file, is the same license as for the pristine package itself (unless the 
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%global packname  conMItion 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        0.2.1 
Release:        0 
Summary:        Conditional Mutual Information Estimation for Multi-Omics Data 
Group:          Development/Libraries/Other 
License:        GPL-2 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         conMItion_0.2.1.tar.gz 
Requires:       R-base 
 
# %%if 0%%{?sle_version} > 120400 || 0%%{?is_opensuse} 
# # Three others commonly needed 
# BuildRequires:  tex(ae.sty) 
# BuildRequires:  tex(fancyvrb.sty) 
# BuildRequires:  tex(inconsolata.sty) 
# BuildRequires:  tex(natbib.sty) 
# %else 
# BuildRequires:  texlive 
# %endif 
# BuildRequires:  texinfo 
BuildRequires:  fdupes 
BuildRequires:  R-base 
BuildRequires:  gcc gcc-c++ gcc-fortran
 
%description 
The biases introduced in association measures, particularly mutual 
information, are influenced by factors such as tumor purity, mutation 
burden, and hypermethylation. This package provides the estimation of 
conditional mutual information (CMI) and its statistical significance 
with a focus on its application to multi-omics data. Utilizing B-spline 
functions (inspired by Daub et al. (2004) 
<doi:10.1186/1471-2105-5-118>), the package offers tools to estimate 
the association between heterogeneous multi- omics data, while removing 
the effects of confounding factors. This helps to unravel complex 
biological interactions. In addition, it includes methods to evaluate 
the statistical significance of these associations, providing a robust 
framework for multi-omics data integration and analysis. This package 
is ideal for researchers in computational biology, bioinformatics, and 
systems biology seeking a comprehensive tool for understanding 
interdependencies in omics data. 
 
%prep 
%setup -q -c -n %{packname} 
# the next line is needed, because we build without --clean in between two packages 
rm -rf ~/.R  
 
 
%build 
 
%install 
mkdir -p %{buildroot}%{rlibdir} 
%{_bindir}/R CMD INSTALL -l %{buildroot}%{rlibdir} %{packname} 
test -d %{packname}/src && (cd %{packname}/src; rm -f *.o *.so) 
rm -f %{buildroot}%{rlibdir}/R.css 
%fdupes -s %{buildroot}%{rlibdir} 
 
#%%check 
#%%{_bindir}/R CMD check %%{packname} 
 
%files 
%dir %{rlibdir}/%{packname} 
%doc %{rlibdir}/%{packname}/DESCRIPTION
%{rlibdir}/%{packname}/INDEX
%{rlibdir}/%{packname}/Meta
%{rlibdir}/%{packname}/NAMESPACE
%{rlibdir}/%{packname}/R
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%{rlibdir}/%{packname}/libs
 
%changelog