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Faith Okamoto edited this page Jul 15, 2026
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Welcome to the vg wiki!
In a hurry? Check our Quickstart guide.
Variation graphs are powerful objects capable of describing populations of genomes. vg provides a set of tools to construct, manipulate, and visualize them in the context of genome informatics.
Please feel free to edit and extend this wiki! For any questions or concerns please use the issues page in this repository, or drop by the vg chat on gitter or irc (#vg in freenode).
- Formats:
- Basic Operations
- Working with Long Reads
- Haplotype Sampling
- Troubleshooting
- Programming with the vg API
- Path Metadata Model
- Creating a graph from two E. coli assemblies: Graph & annotations for two E. coli strains
- Large genomes, from graph construction to read alignment: Working with a whole genome variation graph
- Linear vs. pangenome alignment comparisons: Evaluating alignment performance using simulation
- Construction examples
- Automatic index construction
- Manual index construction
- Building and manipulating GBWTs with vg gbwt
- Dealing with huge datasets
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vg giraffe: Mapping short reads with Giraffe -
vg giraffe: Mapping long reads with Giraffe -
vg giraffe: Giraffe best practices -
vg giraffe: Mapping to a personalized reference with Haplotype Sampling -
vg mpmap: Multipath alignments and vg mpmap
- Visualizing graphs:
- SV genotyping and variant calling
- Simulating reads with vg sim
- Transcriptomic analyses and RNASeq
- Long‐read RNA‐seq with pre‐existing pangenome
- Changing references (How to modify which paths in a GBWT or GBZ are considered a "reference")
- Linear references and vg
- VCF export with vg deconstruct
- Getting alignment statistics with vg filter
- RDF:-for-VG