I'm a starting my analysis on nanopore whole genome sequencing. I start my analysis from this popular Github.

The sample I downloaded was WGS for NA12878, so I would assume it's alignment to GRCh38 shouldn't be that bad.

But ... I'm getting lot's of insertions...

enter image description here

I'm not sure it was caused by the sequencing platform, the MiniMap aligner or my bugs.

I supply all my commands, starting from sample download.

wget https://s3.amazonaws.com/nanopore-human-wgs/rel5-guppy-0.3.0-chunk10k.fastq.gz
gunzip rel5-guppy-0.3.0-chunk10k.fastq.gz
wget http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/technical/reference/GRCh38_reference_genome/GRCh38_full_analysis_set_plus_decoy_hla.fa
minimap2 -d GRCh38_full_analysis_set_plus_decoy_hla.fa.index GRCh38_full_analysis_set_plus_decoy_hla.fa
minimap2 -ax map-ont -t 20 GRCh38_full_analysis_set_plus_decoy_hla.fa.index rel5-guppy-0.3.0-chunk10k.fastq | samtools view -bS - | samtools sort -@ 5 > rel5-guppy-0.3.0-chunk10k.bam 
samtools index rel5-guppy-0.3.0-chunk10k.bam

1 Answer 1


Insertions and deletions are the dominant error mode of long read sequencing, including nanopore sequencing. What you see is not unexpected. Things may have improved by now if you would download the raw fast5 data and repeat the basecalling. There is no need to gunzip the fastq.gz prior to alignment. Your commands for alignment look alright, except that (if you are using a recent version of samtools) you don't really need samtools view and can pipe directly to samtools sort, using -o to specify the output format:

minimap2 -ax map-ont -t 20 <index> <fastq> | samtools sort -@5 -o alignment.bam 

In a recent version of igv you can right-click the alignment and chose a "Quick consensus mode" (or something like that), which will make your alignments at least a bit prettier. Note how the consensus sequence (top of the graph) is quite clean - while individual reads may be noisy this is mostly randomly distributed and as such ironed out in consensus.


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