https://github.com/carrascomj/ripkmer
Playing around with kmers very fast!
https://github.com/carrascomj/ripkmer
bioinformatics kmer rust rust-bio
Last synced: 6 months ago
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Playing around with kmers very fast!
- Host: GitHub
- URL: https://github.com/carrascomj/ripkmer
- Owner: carrascomj
- License: mit
- Created: 2020-02-23T19:46:18.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2020-04-15T07:30:57.000Z (over 5 years ago)
- Last Synced: 2025-02-14T18:38:10.570Z (8 months ago)
- Topics: bioinformatics, kmer, rust, rust-bio
- Language: Rust
- Size: 20.5 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# ripkmer
[](https://travis-ci.com/carrascomj/ripkmer)
There are two ways of viewing this:
- Some k-mer algorithms using [Rust-Bio](https://github.com/rust-bio/rust-bio/) [[1]](#koster2016).
- My first project in Rust just to get confident with it.
## Features
The first idea is to reproduce in Rust the [KmerFinder](https://bitbucket.org/genomicepidemiology/kmerfinder/src/master/) [[2]](#kmerfinder2014)
(in Python, but also in [JavaScript](https://github.com/yosoyubik/kmerfinderjs-docker)).
* [x] K-mer count on FASTQ.
* [x] Filter by prefix.
* [ ] Make it work for FASTA and BED files.
* [x] Compare k-mer distribution of two inputs.
* [ ] Move towards a KMA implementation.
## CLI Example
For this example, the first two FASTQ files of
[SRR396636](https://trace.ncbi.nlm.nih.gov/Traces/sra/?run=SRR396636), corresponding
to reads from _Pseudomonas aeruginsa MPAO1/P1_, with 1909263 sequences of ~100 bp each, were downloaded.
Having **ripkmer** installed and in the `$PATH`:
```bash
ripkmer SRR396636.sra_1.fastq SRR396636.sra_2.fastq
```
where the `k` number and the `prefix` would be left as default, being equivalent
to:
```bash
ripkmer SRR396636.sra_1.fastq SRR396636.sra_2.fastq 16 ATGAC
```
The output is in tabular format and can be redirected to standard output (and should not take much more than 4s).
(16-mers) Unique Redundant Intersection_unique Intersection
SRR396636.sra_1.fastq 23196 97871 34.19% 58.81%
SRR396636.sra_2.fastq 30698 89107 25.83% 64.59%
where
- **Unique** is the number of unique k-mers found in the file;
- **Redundant** is the number of total k-mers found (with repetitions);
- **Interesection_unique** is the number of common unique k-mers found in both files;
- and **Intersection** is the number of total common k-mers found.
## References
[1] Köster, J. (2016). Rust-Bio: a fast and safe bioinformatics library. Bioinformatics, 32(3), 444-446.
[2] Benchmarking of Methods for Genomic Taxonomy. Larsen MV, Cosentino S, Lukjancenko O, Saputra D, Rasmussen S, Hasman H, Sicheritz-Pontén T, Aarestrup FM, Ussery DW, Lund O. J Clin Microbiol. 2014 Feb 26