Note: the most recent version of this vignette can be found here and a short overview slide show here.
systemPipeRdata is a helper package to generate with a single command NGS workflow templates that are intended to be used by its parent package systemPipeR (Girke 2014). The latter is an environment for building end-to-end analysis pipelines with automated report generation for next generation sequence (NGS) applications such as RNA-Seq, Ribo-Seq, ChIP-Seq, VAR-Seq and many others. The directory structure of the workflow templates and the sample data used by systemPipeRdata are described here.
systemPipeRdata can be downloaded from CRAN. The systemPipeRdata package can be installed from within R as follows: zR`{r install, eval=FALSE} source(“http://bioconductor.org/biocLite.R”) # Sources the biocLite.R installation script biocLite(“tgirke/systemPipeRdata”, build_vignettes=TRUE, dependencies=TRUE) # Installs from github biocLite(“systemPipeRdata”) # Installs from Bioconductor once available there ```
library("systemPipeRdata") # Loads the packagelibrary(help="systemPipeRdata") # Lists package info
vignette("systemPipeRdata") # Opens vignetteLoad one of the available NGS workflows into your current working directory. The following does this for the varseq template. The name of the resulting workflow directory can be specified under the mydirname argument. The default NULL uses the name of the chosen workflow. An error is issued if a directory of the same name and path exists already.
genWorkenvir(workflow="varseq", mydirname=NULL)
setwd("varseq")On Linux and OS X systems the same can be achieved from the command-line of a terminal with the following commands. {.sh generate_workenvir_from_shell, eval=FALSE} $ Rscript -e "systemPipeRdata::genWorkenvir(workflow='varseq', mydirname=NULL)"
The workflow templates generated by genWorkenvir contain the following preconfigured directory structure:
workflow_name/ # *.Rnw/*.Rmd scripts and targets file
param/ # parameter files for command-line software
data/ # inputs e.g. FASTQ, reference, annotations
results/ # analysis result filesNext, run from within R the chosen sample workflow by executing the code provided in the corresponding *.Rnw template file. If preferred the corresponding *.Rmd or *.R versions can be used instead. Alternatively, one can run an entire workflow from start to finish with a single command by executing from the command-line 'make -B' within the workflow directory (here 'varseq'). Much more detailed information on running and customizing systemPipeR workflows is available in its overview vignette here. This vignette can also be opened from R with the following command.
library("systemPipeR") # Loads systemPipeR which needs to be installed via biocLite() from Bioconductor vignette("systemPipeR", package = "systemPipeR")The location of the sample data provided by systemPipeRdata can be returned as a list.
pathList()## $targets
## [1] "/tmp/Rtmpb7VM8D/Rinst35e8255055c9/systemPipeRdata/extdata/param/targets.txt"
##
## $targetsPE
## [1] "/tmp/Rtmpb7VM8D/Rinst35e8255055c9/systemPipeRdata/extdata/param/targetsPE.txt"
##
## $annotationdir
## [1] "/tmp/Rtmpb7VM8D/Rinst35e8255055c9/systemPipeRdata/extdata/annotation/"
##
## $fastqdir
## [1] "/tmp/Rtmpb7VM8D/Rinst35e8255055c9/systemPipeRdata/extdata/fastq/"
##
## $bamdir
## [1] "/tmp/Rtmpb7VM8D/Rinst35e8255055c9/systemPipeRdata/extdata/bam/"
##
## $paramdir
## [1] "/tmp/Rtmpb7VM8D/Rinst35e8255055c9/systemPipeRdata/extdata/param/"
##
## $workflows
## [1] "/tmp/Rtmpb7VM8D/Rinst35e8255055c9/systemPipeRdata/extdata/workflows/"
##
## $chipseq
## [1] "/tmp/Rtmpb7VM8D/Rinst35e8255055c9/systemPipeRdata/extdata/workflows/chipseq/"
##
## $rnaseq
## [1] "/tmp/Rtmpb7VM8D/Rinst35e8255055c9/systemPipeRdata/extdata/workflows/rnaseq/"
##
## $riboseq
## [1] "/tmp/Rtmpb7VM8D/Rinst35e8255055c9/systemPipeRdata/extdata/workflows/riboseq/"
##
## $varseq
## [1] "/tmp/Rtmpb7VM8D/Rinst35e8255055c9/systemPipeRdata/extdata/workflows/varseq/"sessionInfo()## R version 3.4.2 (2017-09-28)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 16.04.3 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.6-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.6-bioc/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8
## [4] LC_COLLATE=C LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C
## [10] LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats4 parallel stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] systemPipeRdata_1.6.0 systemPipeR_1.12.0 ShortRead_1.36.0
## [4] GenomicAlignments_1.14.0 SummarizedExperiment_1.8.0 DelayedArray_0.4.0
## [7] matrixStats_0.52.2 Biobase_2.38.0 BiocParallel_1.12.0
## [10] Rsamtools_1.30.0 Biostrings_2.46.0 XVector_0.18.0
## [13] GenomicRanges_1.30.0 GenomeInfoDb_1.14.0 IRanges_2.12.0
## [16] S4Vectors_0.16.0 BiocGenerics_0.24.0 BiocStyle_2.6.0
##
## loaded via a namespace (and not attached):
## [1] edgeR_3.20.0 RMySQL_0.10.13 bit64_0.9-7 splines_3.4.2
## [5] assertthat_0.2.0 latticeExtra_0.6-28 RBGL_1.54.0 blob_1.1.0
## [9] GenomeInfoDbData_0.99.1 yaml_2.1.14 Category_2.44.0 progress_1.1.2
## [13] RSQLite_2.0 backports_1.1.1 lattice_0.20-35 limma_3.34.0
## [17] digest_0.6.12 checkmate_1.8.5 RColorBrewer_1.1-2 colorspace_1.3-2
## [21] htmltools_0.3.6 Matrix_1.2-11 plyr_1.8.4 GSEABase_1.40.0
## [25] pkgconfig_2.0.1 XML_3.98-1.9 pheatmap_1.0.8 biomaRt_2.34.0
## [29] genefilter_1.60.0 bookdown_0.5 zlibbioc_1.24.0 GO.db_3.4.2
## [33] xtable_1.8-2 scales_0.5.0 brew_1.0-6 tibble_1.3.4
## [37] annotate_1.56.0 ggplot2_2.2.1 GenomicFeatures_1.30.0 lazyeval_0.2.1
## [41] survival_2.41-3 magrittr_1.5 memoise_1.1.0 evaluate_0.10.1
## [45] fail_1.3 hwriter_1.3.2 GOstats_2.44.0 graph_1.56.0
## [49] tools_3.4.2 prettyunits_1.0.2 BBmisc_1.11 stringr_1.2.0
## [53] sendmailR_1.2-1 munsell_0.4.3 locfit_1.5-9.1 AnnotationDbi_1.40.0
## [57] compiler_3.4.2 rlang_0.1.2 grid_3.4.2 RCurl_1.95-4.8
## [61] rjson_0.2.15 AnnotationForge_1.20.0 base64enc_0.1-3 bitops_1.0-6
## [65] rmarkdown_1.6 codetools_0.2-15 gtable_0.2.0 DBI_0.7
## [69] R6_2.2.2 knitr_1.17 rtracklayer_1.38.0 bit_1.1-12
## [73] rprojroot_1.2 Rgraphviz_2.22.0 stringi_1.1.5 BatchJobs_1.6
## [77] Rcpp_0.12.13This project was supported by funds from the National Institutes of Health (NIH) and the National Science Foundation (NSF).
Girke, Thomas. 2014. “systemPipeR: NGS Workflow and Report Generation Environment.” UC Riverside. https://github.com/tgirke/systemPipeR.