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HPRC PanGenie results

Authors: Ebler, Jana;

HPRC PanGenie results

Abstract

HPRC PanGenie results Input VCF used for PanGenie for the HPRC experiments as well as genotyping results, statistics and filters computed. All experiments are based on the Minigraph-Cactus (MC) graph. Experiments were run at Heinrich-Heine University Düsseldorf by Jana Ebler (ebler@hhu.de). Pipelines used to produce these results are here: http://bitbucket.org/jana_ebler/hprc-experiments/src/master/genotyping-experiments/ How to run PanGenie on the MC variants We ran PanGenie using the file "cactus_filtered_ids.vcf.gz" as input (contained in this repository). It was produced from the file "hprc-v1.0-mc-grch38.vcf.gz" generated from the MC graph using vg decompose. The output VCF generated by PanGenie can be converted into a bi-allelic VCF containing a single record for each (nested) variant allele, i.e. after decomposing large bubbles into their nested variants using the script: https://bitbucket.org/jana_ebler/hprc-experiments/src/master/genotyping-experiments/workflow/scripts/convert-to-biallelic.py # run PanGenie, produces genotyped VCF "pangenie_genotyping.vcf" PanGenie -i <input-reads> -v cactus_filtered_ids.vcf -r <reference-genome> -o pangenie -j 24 -t 24 # decompose bubbles and produce a bi-allelic VCF with genotypes for each (nested) allele cat pangenie_genotyping.vcf | python3 convert-to-biallelic.py cactus_filtered_ids_biallelic.vcf > pangenie_genotyping_biallelic.vcf

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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