%global __brp_check_rpaths %{nil}
%global __requires_exclude ^libmpi
%global packname  SlimR
%global packver   1.0.8
%global rlibdir   /usr/local/lib/R/library

Name:             R-CRAN-%{packname}
Version:          1.0.8
Release:          1%{?dist}%{?buildtag}
Summary:          Machine Learning-Assisted, Marker-Based Tool for Single-Cell and Spatial Transcriptomics Annotation

License:          MIT + file LICENSE
URL:              https://cran.r-project.org/package=%{packname}
Source0:          %{url}&version=%{packver}#/%{packname}_%{packver}.tar.gz


BuildRequires:    R-devel >= 3.5
Requires:         R-core >= 3.5
BuildArch:        noarch
BuildRequires:    R-CRAN-cowplot 
BuildRequires:    R-CRAN-dplyr 
BuildRequires:    R-CRAN-ggplot2 
BuildRequires:    R-CRAN-patchwork 
BuildRequires:    R-CRAN-pheatmap 
BuildRequires:    R-CRAN-readxl 
BuildRequires:    R-CRAN-scales 
BuildRequires:    R-CRAN-Seurat 
BuildRequires:    R-CRAN-tidyr 
BuildRequires:    R-tools 
BuildRequires:    R-CRAN-tibble 
Requires:         R-CRAN-cowplot 
Requires:         R-CRAN-dplyr 
Requires:         R-CRAN-ggplot2 
Requires:         R-CRAN-patchwork 
Requires:         R-CRAN-pheatmap 
Requires:         R-CRAN-readxl 
Requires:         R-CRAN-scales 
Requires:         R-CRAN-Seurat 
Requires:         R-CRAN-tidyr 
Requires:         R-tools 
Requires:         R-CRAN-tibble 

%description
Annotates single-cell and spatial-transcriptomic (ST) data using marker
datasets. Supports unified markers list ('Markers_list') creation from
built-in databases (e.g., 'Cellmarker2', 'PanglaoDB', 'scIBD', 'TCellSI'),
Seurat objects, or user-supplied Excel files. SlimR can predict calculate
parameters by machine learning algorithms (e.g., 'Random Forest',
'Gradient Boosting', 'Support Vector Machine', 'Ensemble Learning'), and
based on Markers_list, calculate gene expression of different cell types
and predict annotation information and calculate corresponding AUC and
annotate it, then verify it. At the same time, it can calculate gene
expression corresponding to the cell type to generate a reference map for
manual annotation (e.g., 'Heat Map', 'Feature Plots', 'Combined Plots').
For more details see Kabacoff (2020, ISBN:9787115420572).

%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}