|
|
--- |
|
|
license: mit |
|
|
tags: |
|
|
- dna |
|
|
- biology |
|
|
- genomics |
|
|
--- |
|
|
# Processed whole-genome alignment of 100 vertebrate species |
|
|
For more information check out our [paper](https://www.nature.com/articles/s41587-024-02511-w) and [repository](https://github.com/songlab-cal/gpn). |
|
|
|
|
|
Source data: |
|
|
- MSA was downloaded from http://hgdownload.soe.ucsc.edu/goldenPath/hg38/multiz100way/ |
|
|
- Human sequence was replaced with a newer reference: |
|
|
http://ftp.ensembl.org/pub/release-107/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna_sm.primary_assembly.fa.gz |
|
|
|
|
|
Available MSAs: |
|
|
- `89.zarr.zip` contains human + 89 vertebrates (excluding 10 closest primates) |
|
|
- `99.zarr.zip` contains human + 99 vertebrates |
|
|
|
|
|
Example usage: |
|
|
```python |
|
|
from gpn.data import GenomeMSA |
|
|
|
|
|
genome_msa = GenomeMSA(msa_path) |
|
|
X = genome_msa.get_msa(chrom, start, end, strand="+", tokenize=False) |
|
|
``` |
|
|
|
|
|
Coordinates: |
|
|
- `hg38` assembly |
|
|
- `chrom` should be in `["1", "2", ..., "22", "X", "Y"]` |
|
|
|
|
|
## Streaming (playing, few VEP queries) |
|
|
- Faster setup (no need to download and unzip) |
|
|
- Slower queries (depends on network connection) |
|
|
- Multiple dataloader workers don't seem to work |
|
|
- More CPU memory required to load: 10.41 GB |
|
|
- Recommended if you just want to do a few queries, e.g. VEP for a couple thousand variants |
|
|
- ```python |
|
|
msa_path = "zip:///::https://huggingface.co/datasets/songlab/multiz100way/resolve/main/89.zarr.zip" |
|
|
``` |
|
|
|
|
|
## Local download (training, large-scale VEP) |
|
|
- Requires downloading (34GB) and unzipping (currently quite slow, will try to improve) |
|
|
```bash |
|
|
wget https://huggingface.co/datasets/songlab/multiz100way/resolve/main/89.zarr.zip |
|
|
7z x 89.zarr.zip -o89.zarr # can still take 5 hours with 32 cores, will try to streamline this in the future |
|
|
``` |
|
|
- Update: faster unzipping [here](https://huggingface.co/datasets/lpigou/89.zarr), courtesy of [lpigou](https://huggingface.co/lpigou) |
|
|
- Much faster to query |
|
|
- Can have multiple dataloader workers |
|
|
- Virtually no CPU memory required to load |
|
|
- Recommended for training or VEP for millions of variants |
|
|
- ```python |
|
|
msa_path = "89.zarr" |
|
|
``` |
