HPRC-CHM13 PanGenie results

<strong>HPRC-CHM13 PanGenie results</strong> Input VCF used for PanGenie for the HPRC experiments based on CHM13, as well as genotyping results, statistics and filters computed. All experiments are based on the Minigraph-Cactus (MC) graph. PanGenie v2.1.1 was used. <strong>Note:</strong> PanGenie results for CHM13 provided here are <strong>not</strong> directly comparable to the GRCh38-based ones provided here: https://doi.org/10.5281/zenodo.6797328. While v1.0.0 was used to produce GRCh38-based results, a newer, more accurate version (v2.1.1) was used to produce the CHM13-based results provided here. Experiments were run at Heinrich-Heine University Düsseldorf by Jana Ebler ([e-mail]). Pipelines used to produce these results are here: https://github.com/eblerjana/genotyping-pipelines/tree/main/benchmarking-pipeline <strong>How to run PanGenie on the MC variants</strong> We ran PanGenie using the file "chm13_cactus_filtered_ids.vcf.gz" as input (contained in this repository). It was produced from the file "hprc-v1.0-mc-chm13.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 <pre><code># run PanGenie, produces genotyped VCF "pangenie_genotyping.vcf" PanGenie -i &lt;input-reads&gt; -v chm13_cactus_filtered_ids.vcf -r &lt;reference-genome&gt; -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 chm13_cactus_filtered_ids_biallelic.vcf &gt; pangenie_genotyping_biallelic.vcf</code></pre>