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File R-rtpcr.spec of Package R-rtpcr

# Automatically generated by CRAN2OBS
# 
# Spec file for package rtpcr 
# 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) 2024 SUSE LINUX GmbH, Nuernberg, Germany. 
# 
# All modifications and additions to the file contributed by third parties 
# 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 
# license for the pristine package is not an Open Source License, in which 
# case the license is the MIT License). An "Open Source License" is a 
# license that conforms to the Open Source Definition (Version 1.9) 
# published by the Open Source Initiative. 
#  
# Please submit bugfixes or comments via http://bugs.opensuse.org/ 
# 
 
%global packname  rtpcr 
%global rlibdir   %{_libdir}/R/library 
 
Name:           R-%{packname} 
Version:        1.0.8 
Release:        0 
Summary:        qPCR Data Analysis 
Group:          Development/Libraries/Other 
License:        GPL-3 
URL:            http://cran.r-project.org/web/packages/%{packname} 
Source:         rtpcr_1.0.8.tar.gz 
Requires:       R-base 
Requires:	R-multcomp
Requires:	R-multcompView
Requires:	R-ggplot2
Requires:	R-lmerTest
Requires:	R-purrr
Requires:	R-reshape2
Requires:	R-tidyr
Requires:	R-dplyr
Requires:	R-emmeans
Requires:	R-cli
Requires:	R-generics
Requires:	R-glue
Requires:	R-lifecycle
Requires:	R-magrittr
Requires:	R-pillar
Requires:	R-R6
Requires:	R-rlang
Requires:	R-tibble
Requires:	R-tidyselect
Requires:	R-vctrs
Requires:	R-estimability
Requires:	R-numDeriv
Requires:	R-mvtnorm
Requires:	R-gtable
Requires:	R-isoband
Requires:	R-scales
Requires:	R-withr
Requires:	R-lme4
Requires:	R-TH.data
Requires:	R-sandwich
Requires:	R-plyr
Requires:	R-Rcpp
Requires:	R-stringr
Requires:	R-cpp11
Requires:	R-minqa
Requires:	R-nloptr
Requires:	R-RcppEigen
Requires:	R-fansi
Requires:	R-utf8
Requires:	R-zoo
Requires:	R-farver
Requires:	R-labeling
Requires:	R-munsell
Requires:	R-RColorBrewer
Requires:	R-viridisLite
Requires:	R-stringi
Requires:	R-pkgconfig
Requires:	R-colorspace
Requires:	R-testthat
Requires:	R-brio
Requires:	R-callr
Requires:	R-desc
Requires:	R-digest
Requires:	R-evaluate
Requires:	R-jsonlite
Requires:	R-pkgload
Requires:	R-praise
Requires:	R-processx
Requires:	R-ps
Requires:	R-waldo
Requires:	R-crayon
Requires:	R-fs
Requires:	R-pkgbuild
Requires:	R-rprojroot
Requires:	R-diffobj
Requires:	R-rematch2
 
# %%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: 	R-multcomp
BuildRequires: 	R-multcompView
BuildRequires: 	R-ggplot2
BuildRequires: 	R-lmerTest
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BuildRequires:  gcc gcc-c++ gcc-fortran
 
Suggests:	R-knitr
Suggests:	R-rmarkdown
%description 
Various methods are employed for statistical analysis and graphical 
presentation of real-time PCR (quantitative PCR or qPCR) data. 'rtpcr' 
handles amplification efficiency calculation, statistical analysis and 
graphical representation of real-time PCR data based on up to two 
reference genes. By accounting for amplification efficiency values, 
'rtpcr' was developed using a general calculation method described by 
Ganger et al. (2017) <doi:10.1186/s12859-017-1949-5> and Taylor et al. 
(2019) <doi:10.1016/j.tibtech.2018.12.002>, covering both the Livak and 
Pfaffl methods. Based on the experimental conditions, the functions of 
the 'rtpcr' package use t-test (for experiments with a two-level 
factor), analysis of variance (ANOVA), analysis of covariance (ANCOVA) 
or analysis of repeated measure data to calculate the fold change (FC, 
Delta Delta Ct method) or relative expression (RE, Delta Ct method). 
The functions further provide standard errors and confidence intervals 
for means, apply statistical mean comparisons and present significance. 
To facilitate function application, different data sets were used as 
examples and the outputs were explained. An outstanding feature of 
‘rtpcr’ package is providing publication-ready bar plots with various 
controlling arguments which are further editable by ggplot2 functions. 
The 'rtpcr' package is user-friendly and easy to work with and provides 
an applicable resource for analyzing real-time PCR 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
%{rlibdir}/%{packname}/data
%doc %{rlibdir}/%{packname}/doc
%{rlibdir}/%{packname}/extdata
%doc %{rlibdir}/%{packname}/help
%doc %{rlibdir}/%{packname}/html
%{rlibdir}/%{packname}/
 
%changelog

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File R-rtpcr.spec of Package R-rtpcr

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