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You can't run a web browser directly from your "dumb terminal" command line environment. The FastQC results have to be placed where a web browser can access them. One way to do this is to copy the results back to your laptop, for example by using scp from your computer (read more at Copying files from TACC to your laptop).

For convenience, we put an example FastQC report at this URL:
https://web.corral.tacc.utexas.edu/BioinformaticsResource/CoreNGS/yeast_stuff/Sample_Yeast_L005_R1.cat_fastqc/fastqc_report.html 

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Newer versions of FastQC have slightly different report formats. See this example:
https://web.corral.tacc.utexas.edu/BioinformaticsResource/CoreNGS/reports/wcaar_mqc_report.html

Using MultiQC to consolidate multiple QC reports

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idev -m 120 -N 1 -A OTH21164 -r CoreNGSday3  # or -A TRA23004
# or
idev -m 120 -N 1 -A OTH21164 -p development  # or -A TRA23004

# Load the main BioContainers module if you have not already
module load biocontainers  # may take a while

# Load the multiqc module and ask for its usage information
module load multiqc
multiqc --help | more

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• The -l 50 option says that base 50 should be the last base (i.e., trim down to 50 bases)
• The -Q 33 option specifies how base Qualities on the 4th line of each FASTQ entry are encoded.
  
  • The FASTX Toolkit is an older program written in the time when Illumina base qualities were encoded differently, so its default does not work for modern FASTQ files.
    • These days Illumina base qualities follow the Sanger FASTQ standard (Phred score + 33 to make
    an ASCII character)
    • an ASCII character).
  • This option is not really required here because we're just hard trimming, so the program doesn't have to interpret the quality scores. But the -Q 33 option would be required if you were trimming according to base qualities.
  • Note that the fastq_trimmer help does not document this -Q option! But they do talk about it on their website.

Exercise: compressing fastx_trimmer output

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echo $(( `zcat Sample_H54_miRNA_L004_R1.cat.fastq.gz | wc -l` / 4 ))
# or
zcat Sample_H54_miRNA_L004_R1.cat.fastq.gz | wc -l | awk '{print $1 / 4}'

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echo -n $( zcat Sample_H54_miRNA_L004_R1.cat.fastq.gz | head -2 | tail -1 ) | wc -c

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Now execute cutadapt like this:. Note that the backslash ( \ ) here is just a line continuation character so that we can split a long command onto multiple lines to make it more readable.

export CORENGS=/work/projects/BioITeam/projects/courses/Core_NGS_Tools
mkdir -p $SCRATCH/core_ngs/fastq_prep
cd $SCRATCH/core_ngs/fastq_prep
cp $CORENGS/human_stuff/miRNA_test.fq .

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Now we're going to run cutadapt on the larger FASTQ files, and also perform paired-end adapter trimming on some yeast paired-end RNA-seq data.

Since batch jobs can't be submitted from an idev session, make sure you are back on a login node (just exit the idev session).

First stage the 4 FASTQ files we will work on:

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Next create a batch submission script for your job and submit it to the normal queue with a maximum run time of 2 hours.Since batch jobs can't be submitted from an idev session, make sure you are back on a login node (just exit the idev session)1 hour.

cd $SCRATCH/core_ngs/cutadapt
launcher_creator.py -j cuta.cmds -n cuta -t 01:00:00 -a OTH21164 -q normal 
sbatch --reservation=CoreNGS cuta.slurm
showq -u

# or, if you're not on the reservation:
launcher_creator.py -j cuta.cmds -n cuta -t 01:00:00 -a OTH21164 -q development
sbatch cuta.slurm
showq -u

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