Dna2vec is an open-source library to train distributed representations of variable-length k-mers.
For more information, please refer to the paper: dna2vec: Consistent vector representations of variable-length k-mers
This repo is fork of the original pnpnpn/dna2vec repo. The upgrades are:
nworkers argument, so that you can use more than 4 workersThere's no need to install packages or no need to clone the repository. To run the script just type the following command in terminal
docker run --rm -v $(pwd):/app/data --user 1000 alperyilmaz/dna2vec train_dna2vec.py -c sample_config.yml
The container mounts the working directory, thus files are read in or write out to folders within working directory. Just put your fasta files into a folder and edit config file and then start training.
The sample config file can be as simple as:
inputs: inputs/chr*.fa
k-low: 3
k-high: 5
out-dir: results/
Please refer to hg38-20161219-0153.yml for full blown example. For details about usage, please refer to pnpnpn/dna2vec repo.
New: You can add nworkers argument to take full advantage of available CPUs.
This is not systematic testing results, merely my observations at different platforms
| Hardware | Number of workers | Words/s |
|---|---|---|
| i7-4700HQ CPU @ 2.40GHz (Laptop) | 8 | 242,794 |
| c5.4xlarge | 16 |
This software is licensed under the MIT license
Content type
Image
Digest
Size
315.5 MB
Last updated
over 7 years ago
docker pull alperyilmaz/dna2vec