%global __brp_check_rpaths %{nil} %global __requires_exclude ^libmpi %global packname PopComm %global packver 0.1.0.1 %global rlibdir /usr/local/lib/R/library Name: R-CRAN-%{packname} Version: 0.1.0.1 Release: 1%{?dist}%{?buildtag} Summary: Population-Level Cell-Cell Communication Analysis Tools License: MIT + file LICENSE URL: https://cran.r-project.org/package=%{packname} Source0: %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz BuildRequires: R-devel >= 4.1.0 Requires: R-core >= 4.1.0 BuildArch: noarch BuildRequires: R-CRAN-Seurat >= 4.1.0 BuildRequires: R-CRAN-ggplot2 >= 3.3.0 BuildRequires: R-CRAN-tibble >= 3.0.0 BuildRequires: R-CRAN-igraph >= 2.0.0 BuildRequires: R-CRAN-pbmcapply >= 1.5.0 BuildRequires: R-CRAN-reshape2 >= 1.4.1 BuildRequires: R-CRAN-stringr >= 1.4.0 BuildRequires: R-CRAN-Matrix >= 1.2.0 BuildRequires: R-CRAN-scales >= 1.1.1 BuildRequires: R-CRAN-tidyselect >= 1.1.0 BuildRequires: R-CRAN-pheatmap >= 1.0.12 BuildRequires: R-CRAN-broom >= 1.0.0 BuildRequires: R-CRAN-dplyr >= 1.0.0 BuildRequires: R-CRAN-tidyr >= 1.0.0 BuildRequires: R-CRAN-ggpubr >= 0.6.0 BuildRequires: R-CRAN-purrr >= 0.3.0 BuildRequires: R-CRAN-rlang BuildRequires: R-CRAN-RColorBrewer BuildRequires: R-parallel BuildRequires: R-grDevices Requires: R-CRAN-Seurat >= 4.1.0 Requires: R-CRAN-ggplot2 >= 3.3.0 Requires: R-CRAN-tibble >= 3.0.0 Requires: R-CRAN-igraph >= 2.0.0 Requires: R-CRAN-pbmcapply >= 1.5.0 Requires: R-CRAN-reshape2 >= 1.4.1 Requires: R-CRAN-stringr >= 1.4.0 Requires: R-CRAN-Matrix >= 1.2.0 Requires: R-CRAN-scales >= 1.1.1 Requires: R-CRAN-tidyselect >= 1.1.0 Requires: R-CRAN-pheatmap >= 1.0.12 Requires: R-CRAN-broom >= 1.0.0 Requires: R-CRAN-dplyr >= 1.0.0 Requires: R-CRAN-tidyr >= 1.0.0 Requires: R-CRAN-ggpubr >= 0.6.0 Requires: R-CRAN-purrr >= 0.3.0 Requires: R-CRAN-rlang Requires: R-CRAN-RColorBrewer Requires: R-parallel Requires: R-grDevices %description Facilitates population-level analysis of ligand-receptor (LR) interactions using large-scale single-cell transcriptomic data. Identifies significant LR pairs and quantifies their interactions through correlation-based filtering and projection score computations. Designed for large-sample single-cell studies, the package employs statistical modeling, including linear regression, to investigate LR relationships between cell types. It provides a systematic framework for understanding cell-cell communication, uncovering regulatory interactions and signaling mechanisms. Offers tools for LR pair-level, sample-level, and differential interaction analyses, with comprehensive visualization support to aid biological interpretation. The methodology is described in a manuscript currently under review and will be referenced here once published or publicly available. %prep %setup -q -c -n %{packname} # fix end of executable files find -type f -executable -exec grep -Iq . {} \; -exec sed -i -e '$a\' {} \; # prevent binary stripping [ -d %{packname}/src ] && find %{packname}/src -type f -exec \ sed -i 's@/usr/bin/strip@/usr/bin/true@g' {} \; || true [ -d %{packname}/src ] && find %{packname}/src/Make* -type f -exec \ sed -i 's@-g0@@g' {} \; || true # don't allow local prefix in executable scripts find -type f -executable -exec sed -Ei 's@#!( )*/usr/local/bin@#!/usr/bin@g' {} \; %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 # remove buildroot from installed files find %{buildroot}%{rlibdir} -type f -exec sed -i "s@%{buildroot}@@g" {} \; %files %{rlibdir}/%{packname}