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https://github.com/pangenome/impg
implicit pangenome graph
https://github.com/pangenome/impg
Last synced: 28 days ago
JSON representation
implicit pangenome graph
- Host: GitHub
- URL: https://github.com/pangenome/impg
- Owner: pangenome
- License: mit
- Created: 2024-02-09T22:50:23.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-09-16T02:01:26.000Z (3 months ago)
- Last Synced: 2024-09-17T01:17:22.338Z (3 months ago)
- Language: Rust
- Size: 106 KB
- Stars: 37
- Watchers: 7
- Forks: 5
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-pangenomes - impg
README
# impg: implicit pangenome graph
[](http://bioconda.github.io/recipes/impg/README.html)
Pangenome graphs and whole genome multiple alignments are powerful tools, but they are expensive to build and manipulate.
Often, we would like to be able to break a small piece out of a pangenome without constructing the whole thing.
`impg` lets us do this by projecting sequence ranges through many-way (e.g. all-vs-all) pairwise alignments built by tools like `wfmash` and `minimap2`.
## What does `impg` do?
At its core, `impg` lifts over ranges from a target sequence (used as reference) into the queries (the other sequences aligned to the sequence used as reference) described in alignments.
In effect, it lets us pick up homologous loci from all genomes mapped onto our specific target region.
This is particularly useful when you're interested in comparing a specific genomic region across different individuals, strains, or species in a pangenomic or comparative genomic setting.
The output is provided in BED, BEDPE and PAF formats, making it straightforward to use to extract FASTA sequences for downstream use in multiple sequence alignment (like `mafft`) or pangenome graph building (e.g., `pggb` or `minigraph-cactus`).
## How does it work?
`impg` uses coitrees (implicit interval trees) to provide efficient range lookup over the input alignments.
CIGAR strings are converted to a compact delta encoding.
This approach allows for fast and memory-efficient projection of sequence ranges through alignments.
## Using `impg`
Getting started with `impg` is straightforward. Here's a basic example of how to use the command-line utility:
```bash
impg -p cerevisiae.pan.paf.gz -r S288C#1#chrI:50000-100000 -x
```
Your alignments must use `wfmash` default or `minimap2 --eqx` type CIGAR strings which have `=` for matches and `X` for mismatches. The `M` positional match character is not allowed.
Depending on your alignments, this might result in the following BED file:
```txt
S288C#1#chrI 50000 100000
DBVPG6044#1#chrI 35335 85288
Y12#1#chrI 36263 86288
DBVPG6765#1#chrI 36166 86150
YPS128#1#chrI 47080 97062
UWOPS034614#1#chrI 36826 86817
SK1#1#chrI 52740 102721
```
In this example, `-p` specifies the path to the PAF file, `-r` defines the target range in the format of `seq_name:start-end`, and `-x` requests a *transitive closure* of the matches.
That is, for each collected range, we then find what sequence ranges are aligned onto it.
This is done progressively until we've closed the set of alignments connected to the initial target range.
### Installation
To compile and install `impg` from source, you'll need a recent rust build toolchain and cargo.
1. Clone the repository:
```bash
git clone https://github.com/ekg/impg.git
```
2. Navigate to the `impg` directory:
```bash
cd impg
```
3. Compile the tool (requires rust build tools):
```bash
cargo install --force --path .
```
## Authors
Erik Garrison
Andrea Guarracino
Bryce Kille
## License
MIT