1 Introduction

A central concept for designing workflows within the systemPipeR environment is the use of workflow management containers. systemPipeR adopted the widely used community standard Common Workflow Language (CWL) (Amstutz et al. 2016) for describing analysis workflows in a generic and reproducible manner. Using this community standard in systemPipeR has many advantages. For instance, the integration of CWL allows running systemPipeR workflows from a single specification instance either entirely from within R, from various command line wrappers (e.g., cwl-runner) or from other languages (, e.g., Bash or Python). systemPipeR includes support for both command line and R/Bioconductor software as well as resources for containerization, parallel evaluations on computer clusters along with the automated generation of interactive analysis reports.

An important feature of systemPipeR's CWL interface is that it provides two options to run command line tools and workflows based on CWL. First, one can run CWL in its native way via an R-based wrapper utility for cwl-runner or cwl-tools (CWL-based approach). Second, one can run workflows using CWL’s command line and workflow instructions from within R (R-based approach). In the latter case the same CWL workflow definition files (e.g. .cwl and .yml) are used but rendered and executed entirely with R functions defined by systemPipeR, and thus use CWL mainly as a command line and workflow definition format rather than software to run workflows. In this regard systemPipeR also provides several convenience functions that are useful for designing and debugging workflows, such as a command line rendering function to retrieve the exact command line strings for each data set and processing step prior to running a command line.

This overview introduces how CWL describes command line tools and how to connect them to create workflows. In addition, we will demonstrate how the workflow can be easily scalable with systemPipeR.

2 CWL command line specifications

CWL command line specifications are written in YAML format.

In CWL, files with the extension .cwl define the parameters of a chosen command line step or workflow, while files with the extension .yml define the input variables of command line steps.

Let’s explore the .cwl file:

dir_path <- system.file("extdata/cwl/example/", package="systemPipeR")
cwl <- yaml::read_yaml(file.path(dir_path, "example.cwl"))
  • The cwlVersion component shows the CWL specification version used by the document.
  • The class component shows this document describes a command line tool. Note that CWL has another class, called Workflow which represents a union of one or more command line tools together.
cwl[1:2]
## $cwlVersion
## [1] "v1.0"
## 
## $class
## [1] "CommandLineTool"
  • baseCommand component provides the name of the software that we desire to execute.
cwl[3]
## $baseCommand
## [1] "echo"
  • The inputs section provides the input information to run the tool. Important components of this section are:
    • id: each input has an id describing the input name;
    • type: describe the type of input value (string, int, long, float, double, File, Directory or Any);
    • inputBinding: It is optional. This component indicates if the input parameter should appear on the command line. If this component is missing when describing an input parameter, it will not appear in the command line but can be used to build the command line.
cwl[4]
## $inputs
## $inputs$message
## $inputs$message$type
## [1] "string"
## 
## $inputs$message$inputBinding
## $inputs$message$inputBinding$position
## [1] 1
## 
## 
## 
## $inputs$SampleName
## $inputs$SampleName$type
## [1] "string"
## 
## 
## $inputs$results_path
## $inputs$results_path$type
## [1] "Directory"
  • The outputs section should provide a list of the expected outputs after running the command line tools. Important components of this section are:
    • id: each input has an id describing the output name;
    • type: describe the type of output value (string, int, long, float, double, File, Directory, Any or stdout);
    • outputBinding: This component defines how to set the outputs values. The glob component will define the name of the output value.
cwl[5]
## $outputs
## $outputs$string
## $outputs$string$type
## [1] "stdout"
  • stdout: component to specify a filename to capture standard output. Note here we are using a syntax that takes advantage of the inputs section, using results_path parameter and also the SampleName to construct the output filename.
cwl[6]
## $stdout
## [1] "$(inputs.results_path.basename)/$(inputs.SampleName).txt"

Next, let’s explore the .yml file, which provide the parameter values for all the components we describe above.

For this simple example, we have three parameters defined:

yaml::read_yaml(file.path(dir_path, "example_single.yml"))
## $message
## [1] "Hello World!"
## 
## $SampleName
## [1] "M1"
## 
## $results_path
## $results_path$class
## [1] "Directory"
## 
## $results_path$path
## [1] "./results"

Note that if we define an input component in the .cwl file, this value needs to be also defined here in the .yml file.

2.1 How to connect CWL description files within systemPipeR

SYSargsList container stores all the information and instructions needed for processing a set of input files with a single or many command-line steps within a workflow (i.e. several components of the software or several independent software tools). The SYSargsList object is created and fully populated with the SYSargsList construct function.

The following imports a .cwl file (here example.cwl) for running the echo Hello World example.

HW <- SYSargsList(wf_file="example.cwl", input_file="example_single.yml", dir_path = dir_path)
HW
## Instance of 'SYSargsList': 
##     WF Steps:
##        1. Step_1 (Status: Pending)
## 
cmdlist(HW)
## $Step_1
## $Step_1$defaultid
## $Step_1$defaultid$example
## [1] "echo Hello World! > results/M1.txt"

However, we are limited to run just one command line or one sample in this example. To scale the command line over many samples, a simple solution offered by systemPipeR is to provide a variable for each of the parameters that we want to run with multiple samples.

Let’s explore the example:

yml <- yaml::read_yaml(file.path(dir_path, "example.yml"))
yml
## $message
## [1] "_STRING_"
## 
## $SampleName
## [1] "_SAMPLE_"
## 
## $results_path
## $results_path$class
## [1] "Directory"
## 
## $results_path$path
## [1] "./results"

For the message and SampleName parameter, we are passing a variable connecting with a third file called targets.

Now, let’s explore the targets file structure:

targetspath <- system.file("extdata/cwl/example/targets_example.txt", package="systemPipeR")
read.delim(targetspath, comment.char = "#")
##                Message SampleName
## 1         Hello World!         M1
## 2           Hello USA!         M2
## 3 Hello Bioconcudctor!         M3

The targets file defines all input files or values and sample ids of an analysis workflow. For this example, we have defined a string message for the echo command line tool, in the first column that will be evaluated, and the second column is the SampleName id for each one of the messages. Any number of additional columns can be added as needed.

Users should note here, the usage of targets files is optional when using systemPipeR's new CWL interface. Since for organizing experimental variables targets files are extremely useful and user-friendly. Thus, we encourage users to keep using them.

2.1.1 How to connect the parameter files and targets file information?

The constructor function creates an SYSargsList S4 class object connecting three input files:

- CWL command line specification file (`wf_file` argument);
- Input variables (`input_file` argument);
- Targets file (`targets` argument).

As demonstrated above, the latter is optional for workflow steps lacking input files. The connection between input variables (here defined by input_file argument) and the targets file are defined under the inputvars argument. A named vector is required, where each element name needs to match with column names in the targets file, and the value must match the names of the .yml variables. This is used to replace the CWL variable and construct all the command-line for that particular step.

The variable pattern _XXXX_ is used to distinguish CWL variables that target columns will replace. This pattern is recommended for consistency and easy identification but not enforced.

The following imports a .cwl file (same example demonstrated above) for running the echo Hello World example. However, now we are connecting the variable defined on the .yml file with the targets file inputs.

HW_mul <- SYSargsList(targets=targetspath, 
                      wf_file="example.cwl", input_file="example.yml", dir_path = dir_path, 
                      inputvars = c(Message = "_STRING_", SampleName = "_SAMPLE_"))
HW_mul
## Instance of 'SYSargsList': 
##     WF Steps:
##        1. Step_1 (Status: Pending)
## 
cmdlist(HW_mul)
## $Step_1
## $Step_1$M1
## $Step_1$M1$example
## [1] "echo Hello World! > results/M1.txt"
## 
## 
## $Step_1$M2
## $Step_1$M2$example
## [1] "echo Hello USA! > results/M2.txt"
## 
## 
## $Step_1$M3
## $Step_1$M3$example
## [1] "echo Hello Bioconcudctor! > results/M3.txt"
Figure 1: Connectivity between CWL param files and targets files.

Figure 1: Connectivity between CWL param files and targets files.

3 Creating the CWL param files from the command line

Users need to define the command line in a pseudo-bash script format:

command <- "
hisat2 \
    -S <F, out: ./results/M1A.sam> \
    -x <F: ./data/tair10.fasta> \
    -k <int: 1> \
    -min-intronlen <int: 30> \
    -max-intronlen <int: 3000> \
    -threads <int: 4> \
    -U <F: ./data/SRR446027_1.fastq.gz>
"

3.1 Define prefix and defaults

  • First line is the base command. Each line is an argument with its default value.

  • For argument lines (starting from the second line), any word before the first space with leading - or -- in each will be treated as a prefix, like -S or --min. Any line without this first word will be treated as no prefix.

  • All defaults are placed inside <...>.

  • First argument is the input argument type. F for “File”, “int”, “string” are unchanged.

  • Optional: use the keyword out followed the type with a , comma separation to indicate if this argument is also an CWL output.

  • Then, use : to separate keywords and default values, any non-space value after the : will be treated as the default value.

  • If any argument has no default value, just a flag, like --verbose, there is no need to add any <...>

3.2 createParamFiles Function

createParamFiles function requires the string as defined above as an input.

First of all, the function will print the three components of the cwl file: - BaseCommand: Specifies the program to execute. - Inputs: Defines the input parameters of the process. - Outputs: Defines the parameters representing the output of the process.

The four component is the original command line.

If in interactive mode, the function will verify that everything is correct and will ask you to proceed. Here, the user can answer “no” and provide more information at the string level. Another question is to save the param created here.

If running the workflow in non-interactive mode, the createParamFiles function will consider “yes” and returning the container.

cmd <- createParamFiles(command, writeParamFiles = FALSE) 
## *****BaseCommand*****
## hisat2 
## *****Inputs*****
## S:
##     type: File
##     preF: -S
##     yml: ./results/M1A.sam
## x:
##     type: File
##     preF: -x
##     yml: ./data/tair10.fasta
## k:
##     type: int
##     preF: -k
##     yml: 1
## min-intronlen:
##     type: int
##     preF: -min-intronlen
##     yml: 30
## max-intronlen:
##     type: int
##     preF: -max-intronlen
##     yml: 3000
## threads:
##     type: int
##     preF: -threads
##     yml: 4
## U:
##     type: File
##     preF: -U
##     yml: ./data/SRR446027_1.fastq.gz
## *****Outputs*****
## output1:
##     type: File
##     value: ./results/M1A.sam
## *****Parsed raw command line*****
## hisat2 -S ./results/M1A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446027_1.fastq.gz

If the user chooses not to save the param files on the above operation, it can use the writeParamFiles function.

writeParamFiles(cmd, overwrite = TRUE)

3.3 How to access and edit param files

3.3.2 Subsetting the command line

cmd2 <- subsetParam(cmd, position = "inputs", index = 1:2, trim = TRUE)
## *****Inputs*****
## S:
##     type: File
##     preF: -S
##     yml: ./results/M1A.sam
## x:
##     type: File
##     preF: -x
##     yml: ./data/tair10.fasta
## *****Parsed raw command line*****
## hisat2 -S ./results/M1A.sam -x ./data/tair10.fasta
cmdlist(cmd2)
## $defaultid
## $defaultid$hisat2
## [1] "hisat2 -S ./results/M1A.sam -x ./data/tair10.fasta"
cmd2 <- subsetParam(cmd, position = "inputs", index = c("S", "x"), trim = TRUE)
## *****Inputs*****
## S:
##     type: File
##     preF: -S
##     yml: ./results/M1A.sam
## x:
##     type: File
##     preF: -x
##     yml: ./data/tair10.fasta
## *****Parsed raw command line*****
## hisat2 -S ./results/M1A.sam -x ./data/tair10.fasta
cmdlist(cmd2)
## $defaultid
## $defaultid$hisat2
## [1] "hisat2 -S ./results/M1A.sam -x ./data/tair10.fasta"

3.3.3 Replacing a existing argument in the command line

cmd3 <- replaceParam(cmd, "base", index = 1, replace = list(baseCommand = "bwa"))
## Replacing baseCommand
## *****BaseCommand*****
## bwa 
## *****Parsed raw command line*****
## bwa -S ./results/M1A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446027_1.fastq.gz
cmdlist(cmd3)
## $defaultid
## $defaultid$hisat2
## [1] "bwa -S ./results/M1A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446027_1.fastq.gz"
new_inputs <- new_inputs <- list(
    "new_input1" = list(type = "File", preF="-b", yml ="myfile"),
    "new_input2" = "-L <int: 4>"
)
cmd4 <- replaceParam(cmd, "inputs", index = 1:2, replace = new_inputs)
## Replacing inputs
## *****Inputs*****
## new_input1:
##     type: File
##     preF: -b
##     yml: myfile
## new_input2:
##     type: int
##     preF: -L
##     yml: 4
## k:
##     type: int
##     preF: -k
##     yml: 1
## min-intronlen:
##     type: int
##     preF: -min-intronlen
##     yml: 30
## max-intronlen:
##     type: int
##     preF: -max-intronlen
##     yml: 3000
## threads:
##     type: int
##     preF: -threads
##     yml: 4
## U:
##     type: File
##     preF: -U
##     yml: ./data/SRR446027_1.fastq.gz
## *****Parsed raw command line*****
## hisat2 -b myfile -L 4 -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446027_1.fastq.gz
cmdlist(cmd4)
## $defaultid
## $defaultid$hisat2
## [1] "hisat2 -b myfile -L 4 -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446027_1.fastq.gz"

3.3.4 Adding new arguments

newIn <- new_inputs <- list(
    "new_input1" = list(type = "File", preF="-b1", yml ="myfile1"),
    "new_input2" = list(type = "File", preF="-b2", yml ="myfile2"),
    "new_input3" = "-b3 <F: myfile3>"
)
cmd5 <- appendParam(cmd, "inputs", index = 1:2, append = new_inputs)
## Replacing inputs
## *****Inputs*****
## S:
##     type: File
##     preF: -S
##     yml: ./results/M1A.sam
## x:
##     type: File
##     preF: -x
##     yml: ./data/tair10.fasta
## k:
##     type: int
##     preF: -k
##     yml: 1
## min-intronlen:
##     type: int
##     preF: -min-intronlen
##     yml: 30
## max-intronlen:
##     type: int
##     preF: -max-intronlen
##     yml: 3000
## threads:
##     type: int
##     preF: -threads
##     yml: 4
## U:
##     type: File
##     preF: -U
##     yml: ./data/SRR446027_1.fastq.gz
## new_input1:
##     type: File
##     preF: -b1
##     yml: myfile1
## new_input2:
##     type: File
##     preF: -b2
##     yml: myfile2
## new_input3:
##     type: File
##     preF: -b3
##     yml: myfile3
## *****Parsed raw command line*****
## hisat2 -S ./results/M1A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446027_1.fastq.gz -b1 myfile1 -b2 myfile2 -b3 myfile3
cmdlist(cmd5)
## $defaultid
## $defaultid$hisat2
## [1] "hisat2 -S ./results/M1A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446027_1.fastq.gz -b1 myfile1 -b2 myfile2 -b3 myfile3"
cmd6 <- appendParam(cmd, "inputs", index = 1:2, after=0, append = new_inputs)
## Replacing inputs
## *****Inputs*****
## new_input1:
##     type: File
##     preF: -b1
##     yml: myfile1
## new_input2:
##     type: File
##     preF: -b2
##     yml: myfile2
## new_input3:
##     type: File
##     preF: -b3
##     yml: myfile3
## S:
##     type: File
##     preF: -S
##     yml: ./results/M1A.sam
## x:
##     type: File
##     preF: -x
##     yml: ./data/tair10.fasta
## k:
##     type: int
##     preF: -k
##     yml: 1
## min-intronlen:
##     type: int
##     preF: -min-intronlen
##     yml: 30
## max-intronlen:
##     type: int
##     preF: -max-intronlen
##     yml: 3000
## threads:
##     type: int
##     preF: -threads
##     yml: 4
## U:
##     type: File
##     preF: -U
##     yml: ./data/SRR446027_1.fastq.gz
## *****Parsed raw command line*****
## hisat2 -b1 myfile1 -b2 myfile2 -b3 myfile3 -S ./results/M1A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446027_1.fastq.gz
cmdlist(cmd6)
## $defaultid
## $defaultid$hisat2
## [1] "hisat2 -b1 myfile1 -b2 myfile2 -b3 myfile3 -S ./results/M1A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446027_1.fastq.gz"

3.3.5 Editing output param

new_outs <- list(
    "sam_out" = "<F: $(inputs.results_path)/test.sam>"
) 
cmd7 <- replaceParam(cmd, "outputs", index = 1, replace = new_outs)
## Replacing outputs
## *****Outputs*****
## sam_out:
##     type: File
##     value: $(inputs.results_path)/test.sam
## *****Parsed raw command line*****
## hisat2 -S ./results/M1A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446027_1.fastq.gz
output(cmd7) 
## $defaultid
## $defaultid$hisat2
## [1] "./results/test.sam"

3.3.6 Internal Check

cmd <- "
hisat2 \
    -S <F, out: _SampleName_.sam> \
    -x <F: ./data/tair10.fasta> \
    -k <int: 1> \
    -min-intronlen <int: 30> \
    -max-intronlen <int: 3000> \
    -threads <int: 4> \
    -U <F: _FASTQ_PATH1_>
"
WF <- createParamFiles(cmd, overwrite = TRUE, writeParamFiles = TRUE) 
## *****BaseCommand*****
## hisat2 
## *****Inputs*****
## S:
##     type: File
##     preF: -S
##     yml: _SampleName_.sam
## x:
##     type: File
##     preF: -x
##     yml: ./data/tair10.fasta
## k:
##     type: int
##     preF: -k
##     yml: 1
## min-intronlen:
##     type: int
##     preF: -min-intronlen
##     yml: 30
## max-intronlen:
##     type: int
##     preF: -max-intronlen
##     yml: 3000
## threads:
##     type: int
##     preF: -threads
##     yml: 4
## U:
##     type: File
##     preF: -U
##     yml: _FASTQ_PATH1_
## *****Outputs*****
## output1:
##     type: File
##     value: _SampleName_.sam
## *****Parsed raw command line*****
## hisat2 -S _SampleName_.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U _FASTQ_PATH1_ 
##   Written content of 'commandLine' to file: 
##  param/cwl/hisat2/hisat2.cwl 
##   Written content of 'commandLine' to file: 
##  param/cwl/hisat2/hisat2.yml
targetspath <- system.file("extdata", "targets.txt", package = "systemPipeR")
WF_test <- loadWorkflow(targets = targetspath, wf_file="hisat2.cwl",
                   input_file="hisat2.yml", dir_path = "param/cwl/hisat2/")
WF_test <- renderWF(WF_test, inputvars = c(FileName = "_FASTQ_PATH1_", SampleName = "_SampleName_"))
WF_test
## Instance of 'SYSargs2':
##    Slot names/accessors: 
##       targets: 18 (M1A...V12B), targetsheader: 4 (lines)
##       modules: 1
##       wf: 0, clt: 1, yamlinput: 9 (components)
##       input: 18, output: 18
##       cmdlist: 18
##    WF Steps:
##       1. hisat2 (rendered: TRUE)
cmdlist(WF_test)
## $M1A
## $M1A$hisat2
## [1] "hisat2 -S M1A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446027_1.fastq.gz"
## 
## 
## $M1B
## $M1B$hisat2
## [1] "hisat2 -S M1B.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446028_1.fastq.gz"
## 
## 
## $A1A
## $A1A$hisat2
## [1] "hisat2 -S A1A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446029_1.fastq.gz"
## 
## 
## $A1B
## $A1B$hisat2
## [1] "hisat2 -S A1B.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446030_1.fastq.gz"
## 
## 
## $V1A
## $V1A$hisat2
## [1] "hisat2 -S V1A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446031_1.fastq.gz"
## 
## 
## $V1B
## $V1B$hisat2
## [1] "hisat2 -S V1B.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446032_1.fastq.gz"
## 
## 
## $M6A
## $M6A$hisat2
## [1] "hisat2 -S M6A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446033_1.fastq.gz"
## 
## 
## $M6B
## $M6B$hisat2
## [1] "hisat2 -S M6B.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446034_1.fastq.gz"
## 
## 
## $A6A
## $A6A$hisat2
## [1] "hisat2 -S A6A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446035_1.fastq.gz"
## 
## 
## $A6B
## $A6B$hisat2
## [1] "hisat2 -S A6B.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446036_1.fastq.gz"
## 
## 
## $V6A
## $V6A$hisat2
## [1] "hisat2 -S V6A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446037_1.fastq.gz"
## 
## 
## $V6B
## $V6B$hisat2
## [1] "hisat2 -S V6B.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446038_1.fastq.gz"
## 
## 
## $M12A
## $M12A$hisat2
## [1] "hisat2 -S M12A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446039_1.fastq.gz"
## 
## 
## $M12B
## $M12B$hisat2
## [1] "hisat2 -S M12B.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446040_1.fastq.gz"
## 
## 
## $A12A
## $A12A$hisat2
## [1] "hisat2 -S A12A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446041_1.fastq.gz"
## 
## 
## $A12B
## $A12B$hisat2
## [1] "hisat2 -S A12B.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446042_1.fastq.gz"
## 
## 
## $V12A
## $V12A$hisat2
## [1] "hisat2 -S V12A.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446043_1.fastq.gz"
## 
## 
## $V12B
## $V12B$hisat2
## [1] "hisat2 -S V12B.sam -x ./data/tair10.fasta -k 1 -min-intronlen 30 -max-intronlen 3000 -threads 4 -U ./data/SRR446044_1.fastq.gz"

4 Version information

sessionInfo()
## R version 4.1.0 (2021-05-18)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.2 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.13-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.13-bioc/R/lib/libRlapack.so
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_GB              LC_COLLATE=C              
##  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
##  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats4    parallel  stats     graphics  grDevices utils     datasets 
## [8] methods   base     
## 
## other attached packages:
##  [1] DESeq2_1.32.0               magrittr_2.0.1             
##  [3] batchtools_0.9.15           ape_5.5                    
##  [5] ggplot2_3.3.5               systemPipeR_1.26.3         
##  [7] ShortRead_1.50.0            GenomicAlignments_1.28.0   
##  [9] SummarizedExperiment_1.22.0 Biobase_2.52.0             
## [11] MatrixGenerics_1.4.0        matrixStats_0.59.0         
## [13] BiocParallel_1.26.0         Rsamtools_2.8.0            
## [15] Biostrings_2.60.1           XVector_0.32.0             
## [17] GenomicRanges_1.44.0        GenomeInfoDb_1.28.0        
## [19] IRanges_2.26.0              S4Vectors_0.30.0           
## [21] BiocGenerics_0.38.0         BiocStyle_2.20.2           
## 
## loaded via a namespace (and not attached):
##   [1] GOstats_2.58.0           backports_1.2.1          BiocFileCache_2.0.0     
##   [4] systemfonts_1.0.2        GSEABase_1.54.0          splines_4.1.0           
##   [7] digest_0.6.27            htmltools_0.5.1.1        magick_2.7.2            
##  [10] GO.db_3.13.0             fansi_0.5.0              checkmate_2.0.0         
##  [13] memoise_2.0.0            BSgenome_1.60.0          base64url_1.4           
##  [16] limma_3.48.1             annotate_1.70.0          svglite_2.0.0           
##  [19] prettyunits_1.1.1        jpeg_0.1-8.1             colorspace_2.0-2        
##  [22] blob_1.2.1               rvest_1.0.0              rappdirs_0.3.3          
##  [25] xfun_0.24                dplyr_1.0.7              crayon_1.4.1            
##  [28] RCurl_1.98-1.3           jsonlite_1.7.2           graph_1.70.0            
##  [31] genefilter_1.74.0        brew_1.0-6               survival_3.2-11         
##  [34] VariantAnnotation_1.38.0 glue_1.4.2               kableExtra_1.3.4        
##  [37] gtable_0.3.0             zlibbioc_1.38.0          webshot_0.5.2           
##  [40] DelayedArray_0.18.0      V8_3.4.2                 Rgraphviz_2.36.0        
##  [43] scales_1.1.1             pheatmap_1.0.12          DBI_1.1.1               
##  [46] edgeR_3.34.0             Rcpp_1.0.6               viridisLite_0.4.0       
##  [49] xtable_1.8-4             progress_1.2.2           bit_4.0.4               
##  [52] rsvg_2.1.2               AnnotationForge_1.34.0   httr_1.4.2              
##  [55] RColorBrewer_1.1-2       ellipsis_0.3.2           farver_2.1.0            
##  [58] pkgconfig_2.0.3          XML_3.99-0.6             sass_0.4.0              
##  [61] dbplyr_2.1.1             locfit_1.5-9.4           utf8_1.2.1              
##  [64] labeling_0.4.2           tidyselect_1.1.1         rlang_0.4.11            
##  [67] AnnotationDbi_1.54.1     munsell_0.5.0            tools_4.1.0             
##  [70] cachem_1.0.5             generics_0.1.0           RSQLite_2.2.7           
##  [73] evaluate_0.14            stringr_1.4.0            fastmap_1.1.0           
##  [76] yaml_2.2.1               knitr_1.33               bit64_4.0.5             
##  [79] purrr_0.3.4              KEGGREST_1.32.0          RBGL_1.68.0             
##  [82] nlme_3.1-152             formatR_1.11             xml2_1.3.2              
##  [85] biomaRt_2.48.1           debugme_1.1.0            compiler_4.1.0          
##  [88] rstudioapi_0.13          filelock_1.0.2           curl_4.3.2              
##  [91] png_0.1-7                geneplotter_1.70.0       tibble_3.1.2            
##  [94] bslib_0.2.5.1            stringi_1.6.2            highr_0.9               
##  [97] GenomicFeatures_1.44.0   lattice_0.20-44          Matrix_1.3-4            
## [100] vctrs_0.3.8              pillar_1.6.1             lifecycle_1.0.0         
## [103] BiocManager_1.30.16      jquerylib_0.1.4          data.table_1.14.0       
## [106] bitops_1.0-7             rtracklayer_1.52.0       R6_2.5.0                
## [109] BiocIO_1.2.0             latticeExtra_0.6-29      hwriter_1.3.2           
## [112] bookdown_0.22            codetools_0.2-18         assertthat_0.2.1        
## [115] Category_2.58.0          rjson_0.2.20             withr_2.4.2             
## [118] GenomeInfoDbData_1.2.6   hms_1.1.0                grid_4.1.0              
## [121] DOT_0.1                  rmarkdown_2.9            restfulr_0.0.13

5 Funding

This project is funded by NSF award ABI-1661152.

References

Amstutz, Peter, Michael R Crusoe, Nebojša Tijanić, Brad Chapman, John Chilton, Michael Heuer, Andrey Kartashov, et al. 2016. “Common Workflow Language, V1.0,” July. https://doi.org/10.6084/m9.figshare.3115156.v2.