############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD build --keep-empty-dirs --no-resave-data easyRNASeq ### ############################################################################## ############################################################################## * checking for file ‘easyRNASeq/DESCRIPTION’ ... OK * preparing ‘easyRNASeq’: * checking DESCRIPTION meta-information ... OK * installing the package to build vignettes * creating vignettes ... ERROR --- re-building ‘simpleRNASeq.Rmd’ using rmarkdown # Introduction This vignette provides the implementation of the procedure described in point 7 of our __Guidelines for RNA-Seq data analysis__[^1] protocol available from the __Epigenesys__ [website](http://www.epigenesys.eu). Briefly, it details the step necessary to: 1. create a non-redundant annotation 2. count reads per feature 3. pre-analyse the data, i.e. assess the pertinence of the samples' charateristics in the light of their biological provenance; _i.e._ in other words perform a so called _"biological QA"_ using assessment methods such as _Principal Component Analysis_, _Multi-dimensional Scaling_, _Hierarcical Clustering_, _etc._ The aim of this vignette is to go through these steps using the __easyRNASeq__ package, hence the rationale of the implementation will not be discussed, albeit relevant litterature will be pointed at when necessarry. Throughout this vignette we are going to replicate the analysis conducted in Robinson, Delhomme et al.[@Robinson:2014p6362], a study looking at _sexual dimorphism_ in _Eurasian aspen_. To perform the listed steps, we need to instantiate a number of objects to store the minimal set of parameters describing the conducted __RNA-Seq__ experiment, _e.g._ the BAM files location, the annotation location and type, the sequencing parameters, _etc._ To get started with this process, we load the package into our R session: ``` r library(easyRNASeq) ``` before instantiating an __AnnotParam__ object informing on the location and type of the annotation to be used. Quitting from lines 40-41 [vignetteData] (./Chapters/01-Introduction.Rmd) Quitting from lines 30-30 [unnamed-chunk-2] (simpleRNASeq.Rmd) Error: processing vignette 'simpleRNASeq.Rmd' failed with diagnostics: Timeout was reached: [github.com] Resolving timed out after 10057 milliseconds --- failed re-building ‘simpleRNASeq.Rmd’ --- re-building ‘easyRNASeq.Rnw’ using Sweave --- finished re-building ‘easyRNASeq.Rnw’ /Library/Frameworks/R.framework/Resources/bin/R CMD Sweave easyRNASeq.Rnw Output file: easyRNASeq.tex /Library/Frameworks/R.framework/Resources/bin/Rscript -e "tools::texi2pdf('easyRNASeq.tex')" /Library/Frameworks/R.framework/Resources/bin/Rscript -e "rmarkdown::render('simpleRNASeq.Rmd')" processing file: simpleRNASeq.Rmd 1/29 2/29 [style] 3/29 4/29 [unnamed-chunk-1] 5/29 6/29 [unnamed-chunk-2] processing file: ./Chapters/01-Introduction.Rmd 1/5 2/5 [library] 3/5 4/5 [vignetteData] Error in `curl::curl_fetch_memory()`: ! Timeout was reached: [github.com] Resolving timed out after 10141 milliseconds Backtrace: 1. easyRNASeq::vignetteData() 6. easyRNASeq::vignetteData() 8. base::sapply(VIGNETTE.DATA, fetchData) 9. base::lapply(X = X, FUN = FUN, ...) 11. easyRNASeq (local) FUN(X[[i]], ...) ... 17. BiocFileCache:::.httr_get_cache_info(fpath) 19. httr::HEAD(link) 20. httr:::request_perform(req, hu$handle$handle) 22. httr:::request_fetch.write_memory(req$output, req$url, handle) 23. curl::curl_fetch_memory(url, handle = handle) # Introduction This vignette provides the implementation of the procedure described in point 7 of our __Guidelines for RNA-Seq data analysis__[^1] protocol available from the __Epigenesys__ [website](http://www.epigenesys.eu). Briefly, it details the step necessary to: 1. create a non-redundant annotation 2. count reads per feature 3. pre-analyse the data, i.e. assess the pertinence of the samples' charateristics in the light of their biological provenance; _i.e._ in other words perform a so called _"biological QA"_ using assessment methods such as _Principal Component Analysis_, _Multi-dimensional Scaling_, _Hierarcical Clustering_, _etc._ The aim of this vignette is to go through these steps using the __easyRNASeq__ package, hence the rationale of the implementation will not be discussed, albeit relevant litterature will be pointed at when necessarry. Throughout this vignette we are going to replicate the analysis conducted in Robinson, Delhomme et al.[@Robinson:2014p6362], a study looking at _sexual dimorphism_ in _Eurasian aspen_. To perform the listed steps, we need to instantiate a number of objects to store the minimal set of parameters describing the conducted __RNA-Seq__ experiment, _e.g._ the BAM files location, the annotation location and type, the sequencing parameters, _etc._ To get started with this process, we load the package into our R session: ``` r library(easyRNASeq) ``` before instantiating an __AnnotParam__ object informing on the location and type of the annotation to be used. Quitting from lines 40-41 [vignetteData] (./Chapters/01-Introduction.Rmd) Quitting from lines 30-30 [unnamed-chunk-2] (simpleRNASeq.Rmd) Execution halted make: *** [html] Error 1 Error in tools::buildVignettes(dir = ".", tangle = TRUE) : running 'make' failed Execution halted