# Preprocessing of raw SARS-CoV-2 reads

The raw reads available so far are generated from bronchoalveolar lavage fluid (BALF) and are metagenomic in nature: they contain human reads, reads from potential bacterial co-infections as well as true COVID-19 reads.

# Live Resources

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# What's the point?

Assess quality of reads, remove adapters and remove reads mapping to human genome.

# The outline

Illumina and Oxford nanopore reads are pulled from the NCBI SRA (links to SRA accessions are available here (opens new window)). They are then processed separately as described in the workflow section.

# Inputs

💥 If you experience problems downloading data from NCBI SRA, use Galaxy history pre-populated with inputs as described in "Alternate Workflow" section below.

Only SRA accessions are required for this analysis. The described analysis was performed with all SRA SARS-CoV accessions available as of Feb 20, 2020:

  1. Illumina reads

    SRR10903401
    SRR10903402
    SRR10971381
    
  2. Oxford Nanopore reads

    SRR10948550
    SRR10948474
    SRR10902284
    

# Outputs

This workflow produces three outputs that are used in two subsequent analyses:

# Output Used in
1. A combined set of adapter-free Illumina reads without human contamination Assembly
2. A combined set of Oxford Nanopore reads without human contamination Assembly
3. A collection of adapter-free Illumina reads from which human reads have not been removed Variation detection

# The history and the workflow

A Galaxy workspace (history) containing the most current analysis can be imported from here (opens new window).

The publicly accessible workflow (opens new window) can be downloaded and installed on any Galaxy instance. It contains version information for all tools used in this analysis.

The workflow performs the following steps:

# Illumina

  • Illumina reads are QC'ed and adapter sequences are removed using fastp
  • Quality metrics are computed and visualized using fastqc and multiqc
  • Reads are mapped against human genome version hg38 using bwa mem
  • Reads that do not map to hg38 are filtered out using samtools view
  • Reads are converted back to fastq format using samtools fastx

# Oxford nanopore

  • Reads are QC'ed using nanoplot
  • Quality metrics are computed and visualized using fastqc and multiqc
  • Reads are mapped against human genome version hg38 using minimap2
  • Reads that do not map to hg38 are filtered out using samtools view
  • Reads are converted back to fastq format using samtools fastx

# BioConda

Tools used in this analysis are also available from BioConda:

Name Link
sra-tools Anaconda-Server Badge (opens new window)
fastqc Anaconda-Server Badge (opens new window)
multiqc Anaconda-Server Badge (opens new window)
fastp Anaconda-Server Badge (opens new window)
nanoplot Anaconda-Server Badge (opens new window)
bwa Anaconda-Server Badge (opens new window)
picard Anaconda-Server Badge (opens new window)
samtools Anaconda-Server Badge (opens new window)

# Alternate Workflow

An alternate starting point has been created for those not wanting to wait for the data to be downloaded from the NCBI SRA. (This can especially be an issue in Australia or Europe.)

There is a shared history (opens new window) containing all of the starting data in appropriate collections and an alternate workflow (opens new window) able to make use of this alternate input. Apart from a slightly different starting point, the workflow and the outputs it produces are identical to that above.

usegalaxy.org usegalaxy.eu usegalaxy.org.au usegalaxy.be
Input History Input History view view Input History Input History view view Input History Input History view view Input History Input History view view
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