Installation
The R software for running systemPipeR can be downloaded from CRAN. The systemPipeR environment can be installed from R using the biocLite install command. The associated data package systemPipeRdata can be used to generate systemPipeR workflow environments with a single command (see below) containing all parameter files and sample data required to quickly test and run workflows.
source("http://bioconductor.org/biocLite.R") # Sources the biocLite.R installation script
biocLite("systemPipeR") # Installs systemPipeR
biocLite("systemPipeRdata") # Installs systemPipeRdata
Loading package and documentation
library("systemPipeR") # Loads the package
library(help="systemPipeR") # Lists package info
vignette("systemPipeR") # Opens vignette
Load sample data and workflow templates
The mini sample FASTQ files used by this overview vignette as well as the associated workflow reporting vignettes can be loaded via the systemPipeRdata package as shown below. The chosen data set SRP010938 contains 18 paired-end (PE) read sets from Arabidposis thaliana (Howard et al., 2013). To minimize processing time during testing, each FASTQ file has been subsetted to 90,000-100,000 randomly sampled PE reads that map to the first 100,000 nucleotides of each chromosome of the A. thalina genome. The corresponding reference genome sequence (FASTA) and its GFF annotion files (provided in the same download) have been truncated accordingly. This way the entire test sample data set requires less than 200MB disk storage space. A PE read set has been chosen for this test data set for flexibility, because it can be used for testing both types of analysis routines requiring either SE (single end) reads or PE reads.
The following loads one of the available NGS workflow templates (here RNA-Seq) into the user’s current working directory. At the moment, the package includes workflow templates for RNA-Seq, ChIP-Seq, VAR-Seq and Ribo-Seq. Templates for additional NGS applications will be provided in the future.
library(systemPipeRdata)
genWorkenvir(workflow="rnaseq")
setwd("rnaseq")
The working environment of the sample data loaded in previous step contains the following preconfigured directory structure:
- workflow/
- This is the directory of the R session running the workflow.
- Run script ( *.Rnw or *.Rmd) and sample annotation (targets.txt) files are located here.
- Note, this directory can have any name (e.g. rnaseq, varseq). Changing its name does not require any modifications in the run script(s).
- Important subdirectories:
- param/
- Stores parameter files such as: *.param, *.tmpl and *_run.sh.
- data/
- FASTQ samples
- Reference FASTA file
- Annotations
- etc.
- results/
- Alignment, variant and peak files (BAM, VCF, BED)
- Tabular result files
- Images and plots
- etc.
- param/
The sample workflows provided by the package are based on the above directory structure, where directory names are indicated in grey. Users can change this structure as needed, but need to adjust the code in their workflows accordingly.
The following parameter files are included in each workflow template:
targets.txt: initial one provided by user; downstreamtargets_*.txtfiles are generated automatically*.param: defines parameter for input/output file operations, e.g.trim.param,bwa.param,vartools.parm, …*_run.sh: optional bash script, e.g.:gatk_run.sh- Compute cluster environment (skip on single machine):
.BatchJobs: defines type of scheduler forBatchJobs*.tmpl: specifies parameters of scheduler used by a system, e.g. Torque, SGE, StarCluster, Slurm, etc.
Structure of targets file
The targets file defines all input files (e.g. FASTQ, BAM, BCF) and sample comparisons of an analysis workflow. The following shows the format of a sample targets file included in the package. It also can be viewed and downloaded from systemPipeR’s GitHub repository here. In a target file with a single type of input files, here FASTQ files of single end (SE) reads, the first three columns are mandatory including their column names, while it is four mandatory columns for FASTQ files of PE reads. All subsequent columns are optional and any number of additional columns can be added as needed.
Structure of targets file for single end (SE) samples
library(systemPipeR)
targetspath <- system.file("extdata", "targets.txt", package="systemPipeR")
read.delim(targetspath, comment.char = "#")
## FileName SampleName Factor SampleLong Experiment Date
## 1 ./data/SRR446027_1.fastq M1A M1 Mock.1h.A 1 23-Mar-2012
## 2 ./data/SRR446028_1.fastq M1B M1 Mock.1h.B 1 23-Mar-2012
## 3 ./data/SRR446029_1.fastq A1A A1 Avr.1h.A 1 23-Mar-2012
## 4 ./data/SRR446030_1.fastq A1B A1 Avr.1h.B 1 23-Mar-2012
## 5 ./data/SRR446031_1.fastq V1A V1 Vir.1h.A 1 23-Mar-2012
## 6 ./data/SRR446032_1.fastq V1B V1 Vir.1h.B 1 23-Mar-2012
## 7 ./data/SRR446033_1.fastq M6A M6 Mock.6h.A 1 23-Mar-2012
## 8 ./data/SRR446034_1.fastq M6B M6 Mock.6h.B 1 23-Mar-2012
## 9 ./data/SRR446035_1.fastq A6A A6 Avr.6h.A 1 23-Mar-2012
## 10 ./data/SRR446036_1.fastq A6B A6 Avr.6h.B 1 23-Mar-2012
## 11 ./data/SRR446037_1.fastq V6A V6 Vir.6h.A 1 23-Mar-2012
## 12 ./data/SRR446038_1.fastq V6B V6 Vir.6h.B 1 23-Mar-2012
## 13 ./data/SRR446039_1.fastq M12A M12 Mock.12h.A 1 23-Mar-2012
## 14 ./data/SRR446040_1.fastq M12B M12 Mock.12h.B 1 23-Mar-2012
## 15 ./data/SRR446041_1.fastq A12A A12 Avr.12h.A 1 23-Mar-2012
## 16 ./data/SRR446042_1.fastq A12B A12 Avr.12h.B 1 23-Mar-2012
## 17 ./data/SRR446043_1.fastq V12A V12 Vir.12h.A 1 23-Mar-2012
## 18 ./data/SRR446044_1.fastq V12B V12 Vir.12h.B 1 23-Mar-2012
To work with custom data, users need to generate a targets file containing the paths to their own FASTQ files and then provide under targetspath the path to the corresponding targets file.
Structure of targets file for paired end (PE) samples
targetspath <- system.file("extdata", "targetsPE.txt", package="systemPipeR")
read.delim(targetspath, comment.char = "#")[1:2,1:6]
## FileName1 FileName2 SampleName Factor SampleLong Experiment
## 1 ./data/SRR446027_1.fastq ./data/SRR446027_2.fastq M1A M1 Mock.1h.A 1
## 2 ./data/SRR446028_1.fastq ./data/SRR446028_2.fastq M1B M1 Mock.1h.B 1
Sample comparisons
Sample comparisons are defined in the header lines of the targets file starting with ‘# <CMP>’.
readLines(targetspath)[1:4]
## [1] "# Project ID: Arabidopsis - Pseudomonas alternative splicing study (SRA: SRP010938; PMID: 24098335)"
## [2] "# The following line(s) allow to specify the contrasts needed for comparative analyses, such as DEG identification. All possible comparisons can be specified with 'CMPset: ALL'."
## [3] "# <CMP> CMPset1: M1-A1, M1-V1, A1-V1, M6-A6, M6-V6, A6-V6, M12-A12, M12-V12, A12-V12"
## [4] "# <CMP> CMPset2: ALL"
The function readComp imports the comparison information and stores it in a list. Alternatively, readComp can obtain the comparison information from the corresponding SYSargs object (see below).
Note, these header lines are optional. They are mainly useful for controlling comparative analyses according to certain biological expectations, such as identifying differentially expressed genes in RNA-Seq experiments based on simple pair-wise comparisons.
readComp(file=targetspath, format="vector", delim="-")
## $CMPset1
## [1] "M1-A1" "M1-V1" "A1-V1" "M6-A6" "M6-V6" "A6-V6" "M12-A12" "M12-V12" "A12-V12"
##
## $CMPset2
## [1] "M1-A1" "M1-V1" "M1-M6" "M1-A6" "M1-V6" "M1-M12" "M1-A12" "M1-V12" "A1-V1"
## [10] "A1-M6" "A1-A6" "A1-V6" "A1-M12" "A1-A12" "A1-V12" "V1-M6" "V1-A6" "V1-V6"
## [19] "V1-M12" "V1-A12" "V1-V12" "M6-A6" "M6-V6" "M6-M12" "M6-A12" "M6-V12" "A6-V6"
## [28] "A6-M12" "A6-A12" "A6-V12" "V6-M12" "V6-A12" "V6-V12" "M12-A12" "M12-V12" "A12-V12"
Structure of param file and SYSargs container
The param file defines the parameters of a chosen command-line software. The following shows the format of a sample param file provided by this package.
parampath <- system.file("extdata", "tophat.param", package="systemPipeR")
read.delim(parampath, comment.char = "#")
## PairSet Name Value
## 1 modules <NA> bowtie2/2.2.5
## 2 modules <NA> tophat/2.0.14
## 3 software <NA> tophat
## 4 cores -p 4
## 5 other <NA> -g 1 --segment-length 25 -i 30 -I 3000
## 6 outfile1 -o <FileName1>
## 7 outfile1 path ./results/
## 8 outfile1 remove <NA>
## 9 outfile1 append .tophat
## 10 outfile1 outextension .tophat/accepted_hits.bam
## 11 reference <NA> ./data/tair10.fasta
## 12 infile1 <NA> <FileName1>
## 13 infile1 path <NA>
## 14 infile2 <NA> <FileName2>
## 15 infile2 path <NA>
The systemArgs function imports the definitions of both the param file and the targets file, and stores all relevant information in a SYSargs S4 class object. To run the pipeline without command-line software, one can assign NULL to sysma instead of a param file. In addition, one can start the systemPipeR workflow with pre-generated BAM files by providing a targets file where the FileName column gives the paths to the BAM files and sysma is assigned NULL.
args <- suppressWarnings(systemArgs(sysma=parampath, mytargets=targetspath))
args
## An instance of 'SYSargs' for running 'tophat' on 18 samples
Several accessor functions are available that are named after the slot names of the SYSargs object.
names(args)
## [1] "targetsin" "targetsout" "targetsheader" "modules" "software" "cores"
## [7] "other" "reference" "results" "infile1" "infile2" "outfile1"
## [13] "sysargs" "outpaths"
modules(args)
## [1] "bowtie2/2.2.5" "tophat/2.0.14"
cores(args)
## [1] 4
outpaths(args)[1]
## M1A
## "/home/tgirke/Dropbox/Teaching/GEN242/github_course_website/GEN242/vignettes/11_Rworkflows/results/SRR446027_1.fastq.tophat/accepted_hits.bam"
sysargs(args)[1]
## M1A
## "tophat -p 4 -g 1 --segment-length 25 -i 30 -I 3000 -o /home/tgirke/Dropbox/Teaching/GEN242/github_course_website/GEN242/vignettes/11_Rworkflows/results/SRR446027_1.fastq.tophat /home/tgirke/Dropbox/Teaching/GEN242/github_course_website/GEN242/vignettes/11_Rworkflows/data/tair10.fasta ./data/SRR446027_1.fastq ./data/SRR446027_2.fastq"
The content of the param file can also be returned as JSON object as follows (requires rjson package).
systemArgs(sysma=parampath, mytargets=targetspath, type="json")
## [1] "{\"modules\":{\"n1\":\"\",\"v2\":\"bowtie2/2.2.5\",\"n1\":\"\",\"v2\":\"tophat/2.0.14\"},\"software\":{\"n1\":\"\",\"v1\":\"tophat\"},\"cores\":{\"n1\":\"-p\",\"v1\":\"4\"},\"other\":{\"n1\":\"\",\"v1\":\"-g 1 --segment-length 25 -i 30 -I 3000\"},\"outfile1\":{\"n1\":\"-o\",\"v2\":\"<FileName1>\",\"n3\":\"path\",\"v4\":\"./results/\",\"n5\":\"remove\",\"v1\":\"\",\"n2\":\"append\",\"v3\":\".tophat\",\"n4\":\"outextension\",\"v5\":\".tophat/accepted_hits.bam\"},\"reference\":{\"n1\":\"\",\"v1\":\"./data/tair10.fasta\"},\"infile1\":{\"n1\":\"\",\"v2\":\"<FileName1>\",\"n1\":\"path\",\"v2\":\"\"},\"infile2\":{\"n1\":\"\",\"v2\":\"<FileName2>\",\"n1\":\"path\",\"v2\":\"\"}}"