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medaka variant tool (version 1.7.2+galaxy1)

Are you pooling HDF5 datasets?:

Select consensus file(s):

Choose the source for the reference genome:

Using reference genome:

Select genome from the list

Set reference names to limit variant calling:

Separated by ','.

Populate VCF info fields?:

Decode variants at ambiguous reference positions?:

Output VCF records for reference loci predicted to be non-variant?:

Type of VCF to generate:

Variant INFO fields in the VCF can be extended to include allele frequency, depth of coverage, etc., but this requires a BAM dataset to calculate those values from.

BAM to caclulate additional INFO fields from:

Padding width on either side of variant for realignment:

To calculate the additional INFO fields the tool will run medaka tools anntotate, which performs local realignment of the region +- this width around each variant. All calculated new fields will depend on the width chosen, so only change this value if you know what you are doing.

Output log file?:

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 variant decodes probabilities.

Input

reference sequence (FASTA)
(several) consensus files (H5/HDF)

Output

decoded probabilities (VCF)

References

More information are available in the manual and github.