Pipelines to do MinION sequencing of Zika virus

MiSeq pipeline

Here we are using a slightly modified version of the Andersen lab's bioinformatic pipeline.

Data Sync

Data from a completed MiSeq run will be transferred from the Genomics Core to the lab directory on the FHCRC Rhino serve. We can then transfer data to /fh/fast/bedford_t/zika-seq/data/ to a library specific directory.

Data should also be copied onto the sequencing data external hard drive Volumes/Meristem/data/<library>

Note that if you make the directory you may need to update permissions to allow others to access the data. Check the permissions with ls -lah in the new library directory. If necessary, update permissions with chmod 775 which allows the whole lab to have read/write/execute access.

Bioinformatic pipeline

Install the following (easy installs via Homebrew)

brew install samtools
brew install trimmomatic
brew install novoalign

You can have a look at the arguments with man samtools, trimmomatic --help, and novoalign --help.

Trim off primer sequences

Rather than removing primer sequences based on string matching with the actual primer sequences we trim the first 22 bases from the 5' ends of the reads.

We also trim portions of the leading and trailing ends of the reads if those areas do not align well. Leading and trailing regions are trimmed until the quality score of the read exceeds 20.


trimmomatic PE -threads 16  {input.read1} {input.read2} {output.trim1} {output.trim_unpaired1} {output.trim2} {output.trim_unpaired2} ILLUMINACLIP:{input.primer}:2:30:12 LEADING:20 TRAILING:20 SLIDINGWINDOW:4:25 MINLEN:30 HEADCROP:22

Example with sample 569, pool 1:

trimmomatic PE 569-1_S12_L001_R1_001.fastq.gz 569-1_S12_L001_R2_001.fastq.gz 569-1_R1.trimmed.fastq 569-1_R1.trim_unpaired1.fastq 569-1_R2.trimmed.fastq 569-1_R2.trim_unpaired2.fastq ILLUMINACLIP:amplicons_prefix.fa:2:30:12 LEADING:20 TRAILING:20 SLIDINGWINDOW:4:25 MINLEN:30 HEADCROP:22

The vast majority of reads should be in your trimmed fastq files, however because some reads will be unpaired you need to specify an output file for these reads, but they will not be used downstream in the pipeline.

If you are using the exact same multiplex primers as specified in the protocol, then this fasta file should be the file you specify for the ILLUMINACLIP argument. It's formatting is specific to palindrome trimming (see below) so if you are using different primers you'll want to format your file similarly.

Command line arguments:

  • PE specifies paired-end mode.
  • ILLUMINACLIP removes adaptor sequence using palindrome clipping. From the trimmomatic documentation:

'Palindrome' trimming is specifically designed for the case of 'reading through' a short fragment into the adapter sequence on the other end. In this approach, the appropriate adapter sequences are 'in silico ligated' onto the start of the reads, and the combined adapter+read sequences, forward and reverse are aligned. If they align in a manner which indicates 'read-through', the forward read is clipped and the reverse read dropped (since it contains no new data).

  • LEADING and TRAILING species trimming the ends of reads until read quality score reaches 20 or higher.
  • SLIDINGWINDOW specifies the number of bases to average across, here 4 bases and a required quality score of 25.
  • MINLEN will drop any reads that are shorter than the specified integer post crop
  • HEADCROP chomps the first 22 bases, this is what removes the primers.

You can also specify the number of threads to use with -threads.

Trimming occurs in the order of the arguments in the command.

Map reads to reference

Align reads to reference ZIKV genome Zika (GenBank ID: KU853012) using novoalign. Then pipe the output to samtools to get some basic stats about the reads.

Note: you can use a different reference genome, but we recommend that if you are sequencing virus from the Americas that your reference is also from the Americas, and the reference should be a full length genome (>10800 nts) to ensure proper mapping.


novoalign -f {input[0]} {input[1]} -c 16 -r Random -l 40 -g 40 -x 20 -t 502 -d {input[2]} -o SAM | samtools view -F 4 -Sb -o {output}

Example using sample 569, pool 1, read 1 and read 2:

novoalign -f 569-1_R1.trimmed.fastq 569-1_R2.trimmed.fastq -r Random -l 40 -g 40 -x 20 -t 502 -d zika_dc_2016.nix -o SAM | samtools view -F 4 -Sb -o 569-1.trimmed.aligned.bam
  • The reference genome in fasta format is here.
  • The reference genome in novoalign index form is here.

Command line arguments:

  • -f Files containing the read sequences to be aligned. By specifying two files the program treats them as paired end reads.
  • -c specifies the number of threads to use
  • -r sets the rules for handling of reads with multiple alignment locations. Here Random indicates that a single alignment location is randomly chosen from amongst all possible alignment locations.
  • -l sets the minimum read length.
  • -g sets gap opening penalty (we are using default of 40)
  • -x sets gap extension penalty (default is 6, so we are using a higher penalty)
  • -t sets the maximum alignment score acceptable for the best alignment.
  • -o specifies output file type

Aside, if your are interested in looking under the hood a bit more

You can have a look at your BAM file by piping the outout of samtools view to less, e.g.:

samtools view <aligned BAM file> | less -S

The samtools pdf manual provides an explanation for each of the columns of the BAM file.

The FLAG field is an integer, but if translated from arabic form to binary form, provides a bunch of information about the read. The easiest way to do this translation is to type the flag into this tool.

Sort the BAM file and generate an index file (a .bai)

Sort the BAM file using the following command:

samtools sort -T </tmp/aln.sorted> -o <output.sorted.bam> <input.aligned.bam>

An example with sample 569:

samtools sort -T /tmp/aln.sorted -o 569-1.trimmed.aligned.sorted.bam 569-1.trimmed.aligned.bam

You will not be able to generate an index file unless the BAM file has been sorted already. To make the index file call the following command:

samtools index -b <input.sorted.bam> <output.sorted.bai>

Note: if you are going to be analyzing the output in Tablet your index file needs to be named exactly the same as your sorted BAM file with the exception of having the .bai format instead of the .bam.

Merge pool 1 and pool 2 BAM files

To merge the pools together to get your full genome alignment, call:

samtools merge <outfile>.merged.bam <input-pool1>.trimmed.aligned.sorted.bam <input-pool2>.trimmed.aligned.sorted.bam