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medaka variant pipeline (version 1.4.4+galaxy1)

Select input reads:

Read groups are currently ignored, so the bam should only contain reads from a single sample.

Choose the source for the reference genome:

Using reference genome:

Select genome from the list

Set region string(s):

If not provided, will process all contigs.

Select model for initial SNP calling from mixed reads prior to phasing:

For best results it is important to specify the correct model, according to the basecaller used. Medaka models are named to indicate i) the pore type, ii) the sequencing device (MinION or PromethION), iii) the basecaller variant, and iv) the basecaller version

Select model for final variant calling from phased reads:

Set inference batch size:

Set threshold for filtering indels in final VCF:

Set threshold for filtering SNPs in final VCF:

Avoid filtering of final VCF?:

Stop after initial SNP calling from mixed reads prior to phasing?:

Select out file(s)5:

What it does

medaka is a tool suite to create a consensus sequence from nanopore sequencing data.

This task is performed using neural networks applied from a pileup of individual sequencing reads against a draft assembly. It outperforms graph-based methods operating on basecalled data, and can be competitive with state-of-the-art signal-based methods, whilst being much faster.

The module medaka_variant performs a variant calling via neural networks.

Input

It is unlikely that the model arguments should be changed from their defaults.

reads aligned to reference (BAM), should be aligned to the reference against which to call variants
reference (FASTA)

Output

round_0_hap_mixed_phased.bam
round_0_hap_mixed_phased.vcf
round_0_hap_mixed_probs.hdf
round_0_hap_mixed_unphased.vcf
round_1_hap_1_probs.hdf
round_1_hap_1.vcf
round_1_hap_2_probs.hdf
round_1_hap_2.vcf
round_1_phased.vcf
round_1_unfiltered.vcf
round_1.vcf
log

Models

For best results it is important to specify the correct model, -m in the above, according to the basecaller used. Allowed values can be found by running medaka tools list_models.

Medaka models are named to indicate i) the pore type, ii) the sequencing device (MinION or PromethION), iii) the basecaller variant, and iv) the basecaller version, with the format:

{pore}_{device}_{caller variant}_{caller version}

For example the model named r941_min_fast_g303 should be used with data from MinION (or GridION) R9.4.1 flowcells using the fast Guppy basecaller version 3.0.3. By contrast the model r941_prom_hac_g303 should be used with PromethION data and the high accuracy basecaller (termed "hac" in Guppy configuration files). Where a version of Guppy has been used without an exactly corresponding medaka model, the medaka model with the highest version equal to or less than the guppy version should be selected.

References

More information are available in the manual and github.