Nextflow Registry | nf-core/glimpse2/concordance@0.0.0-6c4ed3a

nf-core/glimpse2/concordance @ 0.0.0-6c4ed3a

Program to compute the genotyping error rate at the sample or marker level.

concordance low-coverage glimpse imputation

Latest version: 0.0.0-6c4ed3a

Total downloads: 3

Source: nf-core/modules

Authors: @louislenezet

Maintainers: @louislenezet

Program to compute the genotyping error rate at the sample or marker level.

Add the following snippet to your workflow script to include this module.

include { GLIMPSE2_CONCORDANCE } from 'nf-core/glimpse2/concordance'

MIT License

Process

`Name`	`GLIMPSE2_CONCORDANCE`

Input 2 channels

#1 tuple

`meta` map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]
`estimate` file	Imputed dataset file obtain after phasing. `*.{vcf,bcf,vcf.gz,bcf.gz}`
`estimate_index` file	Index file for the imputed dataset file.
`truth` file	Validation dataset called at the same positions as the imputed file. `*.{vcf,bcf,vcf.gz,bcf.gz}`
`truth_index` file	Index file for the truth file.
`freq` file	File containing allele frequencies at each site. `*.{vcf,bcf,vcf.gz,bcf.gz}`
`freq_index` file	Index file for the allele frequencies file.
`samples` file	List of samples to process, one sample ID per line. `*.{txt,tsv}`
`region` string	Target region used for imputation, including left and right buffers (e.g. chr20:1000000-2000000). Can also be a list of such regions. `chrXX:leftBufferPosition-rightBufferPosition`

#2 tuple

`meta2` map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]
`groups` file	Alternative to frequency bins, group bins are user defined, provided in a file. `*.{txt,tsv}`
`bins` string	Allele frequency bins used for rsquared computations. By default they should as MAF bins [0-0.5], while they should take the full range [0-1] if --use-ref-alt is used. `0 0.01 0.05 ... 0.5`
`ac_bins` string	User-defined allele count bins used for rsquared computations. `1 2 5 10 20 ... 100000`
`allele_counts` string	Default allele count bins used for rsquared computations. AN field must be defined in the frequency file.
`min_val_gl` float	Minimum genotype likelihood probability P(G\|R) in validation data. Set to zero to have no filter of if using –gt-validation
`min_val_dp` integer	Minimum coverage in validation data. If FORMAT/DP is missing and –min_val_dp > 0, the program exits with an error. Set to zero to have no filter of if using –gt-validation

Output 7 channels

#1 errors_cal tuple

`meta` map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]
`*.error.cal.txt.gz` file	Calibration correlation errors between imputed dosages (in MAF bins) and highly-confident genotype. `*.errors.cal.txt.gz`

#2 errors_grp tuple

`meta` map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]
`*.error.grp.txt.gz` file	Groups correlation errors between imputed dosages (in MAF bins) and highly-confident genotype. `*.errors.grp.txt.gz`

#3 errors_spl tuple

`meta` map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]
`*.error.spl.txt.gz` file	Samples correlation errors between imputed dosages (in MAF bins) and highly-confident genotype. `*.errors.spl.txt.gz`

#4 rsquare_grp tuple

`meta` map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]
`*.rsquare.grp.txt.gz` file	Groups r-squared correlation between imputed dosages (in MAF bins) and highly-confident genotype. `*.rsquare.grp.txt.gz`

#5 rsquare_spl tuple

`meta` map	Groovy Map containing sample information e.g. [ id:'test', single_end:false ]
`*.rsquare.spl.txt.gz` file	Samples r-squared correlation between imputed dosages (in MAF bins) and highly-confid