Description

Apply a Convolutional Neural Net to filter annotated variants

Input

Name (Type)
Description
Pattern

meta (map)

Groovy Map containing sample information
e.g. [ id:‘test’, single_end

]

vcf (file)

VCF file

*.vcf.gz

tbi (file)

VCF index file

*.vcf.gz.tbi

aligned_input (file)

BAM/CRAM file from alignment (optional)

*.{bam,cram}

intervals (file)

Bed file with the genomic regions included in the library (optional)

fasta (file)

The reference fasta file

*.fasta

fai (file)

Index of reference fasta file

*.fasta.fai

dict (file)

GATK sequence dictionary

*.dict

architecture (file)

Neural Net architecture configuration json file (optional)

*.json

weights (file)

Keras model HD5 file with neural net weights. (optional)

*.hd5

Output

Name (Type)
Description
Pattern

meta (map)

Groovy Map containing sample information
e.g. [ id:‘test’, single_end

]

versions (file)

File containing software versions

versions.yml

vcf (file)

Annotated VCF file

*.vcf

tbi (file)

VCF index file

*.vcf.gz.tbi
included in
sarek
author
Github user FriederikeHanssen
get in touch
Ask a question on Slack Open an issue on GitHub

Tools

gatk4
Apache-2.0

Developed in the Data Sciences Platform at the Broad Institute, the toolkit offers a wide variety of tools with a primary focus on variant discovery and genotyping. Its powerful processing engine and high-performance computing features make it capable of taking on projects of any size.

gatk.broadinstitute.org/hc/en-us gatk.broadinstitute.org/hc/en-us/categories/360002369672s 10.1158/1538-7445.AM2017-3590