https://github.com/mbhall88/skc
Shared k-mer content between two genomes
https://github.com/mbhall88/skc
bioinformatics k-mer
Last synced: about 2 months ago
JSON representation
Shared k-mer content between two genomes
- Host: GitHub
- URL: https://github.com/mbhall88/skc
- Owner: mbhall88
- License: mit
- Created: 2023-06-08T04:24:26.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-06-21T23:06:14.000Z (over 2 years ago)
- Last Synced: 2025-06-28T21:50:30.696Z (4 months ago)
- Topics: bioinformatics, k-mer
- Language: Rust
- Homepage:
- Size: 33.2 KB
- Stars: 18
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
# skc
`skc` is a simple tool for finding shared k-mer content between two genomes.
## Installation
### Prebuilt binary
```
curl -sSL skc.mbh.sh | sh
# or with wget
wget -nv -O - skc.mbh.sh | sh
```
You can also pass options to the script like so
```text
$ curl -sSL skc.mbh.sh | sh -s -- --help
install.sh [option]
Fetch and install the latest version of skc, if skc is already
installed it will be updated to the latest version.
Options
-V, --verbose
Enable verbose output for the installer
-f, -y, --force, --yes
Skip the confirmation prompt during installation
-p, --platform
Override the platform identified by the installer
-b, --bin-dir
Override the bin installation directory [default: /usr/local/bin]
-a, --arch
Override the architecture identified by the installer [default: x86_64]
-B, --base-url
Override the base URL used for downloading releases [default: https://github.com/mbhall88/skc/releases]
-h, --help
Display this help message
```
### Cargo
```text
cargo install skc
```
### Conda
```text
conda install skc
```
### Local
```text
cargo build --release
./target/release/skc --help
```
## Usage
Check for shared 16-mers between the [HIV-1 genome](https://www.ncbi.nlm.nih.gov/nuccore/NC_001802.1) and the [
*Mycobacterium tuberculosis* genome](https://www.ncbi.nlm.nih.gov/nuccore/NC_000962.3).
```text
$ skc -k 16 NC_001802.1.fa NC_000962.3.fa
[2023-06-20T01:46:36Z INFO ] 9079 unique k-mers in target
[2023-06-20T01:46:38Z INFO ] 2 shared k-mers between target and query
>4233642782 tcount=1 qcount=1 tpos=NC_001802.1:739 qpos=NC_000962.3:4008106
TGCAGAACATCCAGGG
>4237062597 tcount=1 qcount=1 tpos=NC_001802.1:8415 qpos=NC_000962.3:629482
CCAGCAGCAGATAGGG
```
So we can see there are two shared 16-mers between the genomes. By default, the shared k-mers are written to stdout -
use the `-o` option to write them to file.
### Fasta description
Example: `>4233642782 tcount=1 qcount=1 tpos=NC_001802.1:739 qpos=NC_000962.3:4008106`
The ID (`4233642782`) is the 64-bit integer representation of the k-mer's value in bit-space (
see [Daniel Liu's brilliant `cute-nucleotides` repository][cute] for more information). `tcount` and `qcount` are the
number of times the k-mer is present in the target and query genomes, respectively. `tpos` and `qpos` are the (1-based)
k-mer starting position(s) within the target and query contigs - these will be comma-seperated if the k-mer occurs
multiple times.
### Usage help
```text
$ skc --help
Shared k-mer content between two genomes
Usage: skc [OPTIONS]
Arguments:
Target sequence
Can be compressed with gzip, bzip2, xz, or zstd
Query sequence
Can be compressed with gzip, bzip2, xz, or zstd
Options:
-k, --kmer
Size of k-mers (max. 32)
[default: 21]
-o, --output
Output filepath(s); stdout if not present
-O, --output-type
u: uncompressed; b: Bzip2; g: Gzip; l: Lzma; z: Zstd
Output compression format is automatically guessed from the filename extension. This option is used to override that
[default: u]
-l, --compress-level
Compression level to use if compressing output
[default: 6]
-h, --help
Print help (see a summary with '-h')
-V, --version
Print version
```
### Caveats
- Make the first genome passed (``) the smallest genome. This is to reduce memory usage as all unique k-mers (
well their `u64` value) for this genome will be held in memory.
- We do not use canonical k-mers
- 32 is the largest k-mer size that can be used. This is basically a (lazy) implementation decision, but also helps to
keep the memory footprint as low as possible. If you want larger k-mer values, I would suggest checking out some of
the [similar tools](#alternate-tools).
## Alternate tools
`skc` does not claim to be the fastest or most memory-efficient tool to find shared k-mer content. I basically wrote it
as I either struggled to install some alternate tools, they were clunky/verbose, or it was laborious to get shared
k-mers out of the results (e.g. can only search one k-mer at a time or have to run many different subcommands). Here is
a (non-exhaustive) list of other tools that can be used to get shared k-mer content
- [unikmer](https://github.com/shenwei356/unikmer) - this was brought to my attention *after* I wrote `skc`. Had I known
about it beforehand, I probably wouldn't have written `skc`. So I would recommend unikmer for almost all use
cases - [Wei Shen](https://github.com/shenwei356) writes awesome tools
- [Jellyfish](https://github.com/gmarcais/Jellyfish)
- [REINDEER](https://github.com/kamimrcht/REINDEER)
- [kmer-db](https://github.com/refresh-bio/kmer-db)
- [GGCAT](https://github.com/algbio/ggcat)
- [KAT](https://github.com/TGAC/KAT)
## Acknowledgements
[Daniel Liu's brilliant `cute-nucleotides` repository][cute] is used to (rapidly) convert k-mers into 64-bit integers.
[cute]: https://github.com/Daniel-Liu-c0deb0t/cute-nucleotides