-# Turning a bash script into a workflow using existing tools
+# Turning a shell script into a workflow by composing existing tools
-In this lesson we will turn `rnaseq_analysis_on_input_file.sh` into a workflow.
+## Introduction
-# Setting up
+The goal of this training is to walk through the development of a
+best-practices CWL workflow by translating an existing bioinformatics
+shell script into CWL. Specific knowledge of the biology of RNA-seq
+is *not* a prerequisite for these lessons.
-We will create a new git repository and import a library of existing
-tool definitions that will help us build our workflow.
+These lessons are based on "Introduction to RNA-seq using
+high-performance computing (HPC)" lessons developed by members of the
+teaching team at the Harvard Chan Bioinformatics Core (HBC). The
+original training, which includes additional lectures about the
+biology of RNA-seq can be found here:
+
+https://github.com/hbctraining/Intro-to-rnaseq-hpc-O2
+
+## Background
+
+RNA-seq is the process of sequencing RNA in a biological sample. From
+the sequence reads, we want to measure the relative number of RNA
+molecules appearing in the sample that were produced by particular
+genes. This analysis is called "differential gene expression".
+
+The entire process looks like this:
+
+
+
+For this training, we are only concerned with the middle analytical
+steps (skipping adapter trimming).
+
+* Quality control (FASTQC)
+* Alignment (mapping)
+* Counting reads associated with genes
+
+## Analysis shell script
-1. Select "Terminal->New terminal"
+This analysis is already available as a Unix shell script, which we
+will refer to in order to build the workflow.
-2. Create a new git repository to hold our workflow with this command:
+Some of the reasons to use CWL over a plain shell script: portability,
+scalability, ability to run on platforms that are not traditional HPC.
-## Arvados
+rnaseq_analysis_on_input_file.sh
```
-git clone https://github.com/arvados/arvados-vscode-cwl-template.git rnaseq-cwl-training-exercises
+#!/bin/bash
+
+# Based on
+# https://hbctraining.github.io/Intro-to-rnaseq-hpc-O2/lessons/07_automating_workflow.html
+#
+
+# This script takes a fastq file of RNA-Seq data, runs FastQC and outputs a counts file for it.
+# USAGE: sh rnaseq_analysis_on_input_file.sh <name of fastq file>
+
+set -e
+
+# initialize a variable with an intuitive name to store the name of the input fastq file
+fq=$1
+
+# grab base of filename for naming outputs
+base=`basename $fq .subset.fq`
+echo "Sample name is $base"
+
+# specify the number of cores to use
+cores=4
+
+# directory with genome reference FASTA and index files + name of the gene annotation file
+genome=rnaseq/reference_data
+gtf=rnaseq/reference_data/chr1-hg19_genes.gtf
+
+# make all of the output directories
+# The -p option means mkdir will create the whole path if it
+# does not exist and refrain from complaining if it does exist
+mkdir -p rnaseq/results/fastqc
+mkdir -p rnaseq/results/STAR
+mkdir -p rnaseq/results/counts
+
+# set up output filenames and locations
+fastqc_out=rnaseq/results/fastqc
+align_out=rnaseq/results/STAR/${base}_
+counts_input_bam=rnaseq/results/STAR/${base}_Aligned.sortedByCoord.out.bam
+counts=rnaseq/results/counts/${base}_featurecounts.txt
+
+echo "Processing file $fq"
+
+# Run FastQC and move output to the appropriate folder
+fastqc $fq
+
+# Run STAR
+STAR --runThreadN $cores --genomeDir $genome --readFilesIn $fq --outFileNamePrefix $align_out --outSAMtype BAM SortedByCoordinate --outSAMunmapped Within --outSAMattributes Standard
+
+# Create BAM index
+samtools index $counts_input_bam
+
+# Count mapped reads
+featureCounts -T $cores -s 2 -a $gtf -o $counts $counts_input_bam
```
-## Generic
+## Setting up
+
+We will create a new git repository and import a library of existing
+tool definitions that will help us build our workflow.
+
+Create a new git repository to hold our workflow with this command:
```
git init rnaseq-cwl-training-exercises
```
+On Arvados use this:
-3. Go to File->Open Folder and select rnaseq-cwl-training-exercises
-
-4. Go to the terminal window
+```
+git clone https://github.com/arvados/arvados-vscode-cwl-template.git rnaseq-cwl-training-exercises
+```
-5. Import bio-cwl-tools with this command:
+Next, import bio-cwl-tools with this command:
```
git submodule add https://github.com/common-workflow-library/bio-cwl-tools.git
```
-# Writing the workflow
+## Writing the workflow
-1. Create a new file "main.cwl"
+### 1. File header
-2. Start with this header.
+Create a new file "main.cwl"
+
+Start with this header.
```
label: RNAseq CWL practice workflow
```
-3. Workflow Inputs
+### 2. Workflow Inputs
The purpose of a workflow is to consume some input parameters, run a
series of steps, and produce output values.
For this analysis, the input parameters are the fastq file and the reference data required by STAR.
-In CWL, these are declared in the `inputs` section.
+In the original shell script, the following variables are declared:
+
+```
+# initialize a variable with an intuitive name to store the name of the input fastq file
+fq=$1
+
+# directory with genome reference FASTA and index files + name of the gene annotation file
+genome=rnaseq/reference_data
+gtf=rnaseq/reference_data/chr1-hg19_genes.gtf
+```
+
+In CWL, we will declare these variables in the `inputs` section.
The inputs section lists each input parameter and its type. Valid
types include `File`, `Directory`, `string`, `boolean`, `int`, and
gtf: File
```
-4. Workflow Steps
+### 3. Workflow Steps
A workflow consists of one or more steps. This is the `steps` section.
fastqc:
run: bio-cwl-tools/fastqc/fastqc_2.cwl
in:
- reads_file: fq
- out: [html_file, summary_file]
+ reads_file: fq
+ out: [html_file]
```
-5. Running alignment with STAR
+### 4. Running alignment with STAR
STAR has more parameters. Sometimes we want to provide input values
to a step without making them as workflow-level inputs. We can do
out: [alignment]
```
-6. Running samtools
+### 5. Running samtools
The third step is to generate an index for the aligned BAM.
out: [bam_sorted_indexed]
```
-7. featureCounts
+### 6. featureCounts
As of this writing, the `subread` package that provides
`featureCounts` is not available in bio-cwl-tools (and if it has been
dive into how to write a CWL wrapper for a command line tool in
lesson 2. For now, we will leave off the final step.
-8. Workflow Outputs
+### 7. Workflow Outputs
The last thing to do is declare the workflow outputs in the `outputs` section.
qc_html:
type: File
outputSource: fastqc/html_file
- qc_summary:
- type: File
- outputSource: fastqc/summary_file
bam_sorted_indexed:
type: File
outputSource: samtools/bam_sorted_indexed
projects / rnaseq-cwl-training.git / blobdiff